mppi_ee7500_proj_oval.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MPPI control of a Differential Drive Robot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tigerwife/Documents/EE_7500_project/python_simple_mppi/scripts/utils.py:46: SyntaxWarning: invalid escape sequence '\\o'\n",
      "  ax2.plot(t_steps,wb_arr, 'r-', label='$\\omega_b$', linewidth=2)\n",
      "/home/tigerwife/Documents/EE_7500_project/python_simple_mppi/scripts/utils.py:49: SyntaxWarning: invalid escape sequence '\\o'\n",
      "  ax2.set_title('u(1): Angular velocity $\\omega_b$')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] delta_t : 0.10[s] , sim_steps : 10000[steps], total_sim_time : 1000.00[s]\n",
      "Step : 0 time: --> 2.893610558986664 s, odometry: - [0.00198648 0.         0.00501045].\n",
      "Step : 1 time: --> 0.24630230700969696 s, odometry: - [1.03804715e-02 4.20580342e-05 8.63032850e-03].\n",
      "Step : 2 time: --> 0.24799040900170802 s, odometry: - [0.02257185 0.00014728 0.01162047].\n",
      "Step : 3 time: --> 0.24624938099086285 s, odometry: - [0.03999861 0.00034979 0.01609994].\n",
      "Step : 4 time: --> 0.24615395699441434 s, odometry: - [0.06222887 0.00070773 0.01815297].\n",
      "Step : 5 time: --> 0.25793380799889565 s, odometry: - [0.08659165 0.00115003 0.02305414].\n",
      "Step : 6 time: --> 0.24249894699454308 s, odometry: - [0.11904963 0.00189846 0.02752698].\n",
      "Step : 7 time: --> 0.2446046340018511 s, odometry: - [0.15282231 0.00282835 0.03557165].\n",
      "Step : 8 time: --> 0.24625248900055885 s, odometry: - [0.18933527 0.00412773 0.04668611].\n",
      "Step : 9 time: --> 0.24499341599643232 s, odometry: - [0.23134369 0.00609036 0.05408888].\n",
      "Step : 10 time: --> 0.24626701699197293 s, odometry: - [0.27803762 0.00861845 0.06424421].\n",
      "Step : 11 time: --> 0.24417102798819543 s, odometry: - [0.32798543 0.01183173 0.07918138].\n",
      "Step : 12 time: --> 0.24199205699563026 s, odometry: - [0.37985528 0.01594746 0.08702651].\n",
      "Step : 13 time: --> 0.2412324810028076 s, odometry: - [0.43583341 0.02083138 0.09592382].\n",
      "Step : 14 time: --> 0.24243805898725987 s, odometry: - [0.49677836 0.02669545 0.10327099].\n",
      "Step : 15 time: --> 0.24405510398745536 s, odometry: - [0.56088357 0.03333929 0.11564202].\n",
      "Step : 16 time: --> 0.24217427299916744 s, odometry: - [0.63118455 0.04150547 0.12165124].\n",
      "Step : 17 time: --> 0.24281240199506282 s, odometry: - [0.7018475  0.05014437 0.12202771].\n",
      "Step : 18 time: --> 0.2433536400049925 s, odometry: - [0.77878164 0.05957934 0.11519164].\n",
      "Step : 19 time: --> 0.24481008300185203 s, odometry: - [0.85944817 0.06891277 0.10885459].\n",
      "Step : 20 time: --> 0.24283568799495697 s, odometry: - [0.94883013 0.07868102 0.10115812].\n",
      "Step : 21 time: --> 0.24248331899940967 s, odometry: - [1.03998492 0.08793365 0.09388932].\n",
      "Step : 22 time: --> 0.24324494801461696 s, odometry: - [1.1358854  0.09696423 0.08372888].\n",
      "Step : 23 time: --> 0.24458402399718762 s, odometry: - [1.23477951 0.10526393 0.0777782 ].\n",
      "Step : 24 time: --> 0.24397089900076388 s, odometry: - [1.33659323 0.11319882 0.07176237].\n",
      "Step : 25 time: --> 0.24339085398614407 s, odometry: - [1.43393565 0.12019636 0.06537954].\n",
      "Step : 26 time: --> 0.24419790299236774 s, odometry: - [1.53716388 0.12695501 0.06060442].\n",
      "Step : 27 time: --> 0.24381301900744437 s, odometry: - [1.64266873 0.13335691 0.06335174].\n",
      "Step : 28 time: --> 0.24495334099233151 s, odometry: - [1.75147143 0.14025899 0.0649422 ].\n",
      "Step : 29 time: --> 0.24644574899971486 s, odometry: - [1.87004824 0.14797047 0.06673659].\n",
      "Step : 30 time: --> 0.2430438870191574 s, odometry: - [1.99208518 0.15612691 0.06951555].\n",
      "Step : 31 time: --> 0.24525118300318718 s, odometry: - [2.12031704 0.16505541 0.06610286].\n",
      "Step : 32 time: --> 0.24417906700074674 s, odometry: - [2.25134712 0.17372951 0.06322868].\n",
      "Step : 33 time: --> 0.24606838200986386 s, odometry: - [2.38395819 0.18212552 0.05892279].\n",
      "Step : 34 time: --> 0.24576493799686433 s, odometry: - [2.51751991 0.19000447 0.04743317].\n",
      "Step : 35 time: --> 0.24413447999954224 s, odometry: - [2.6526299  0.19641798 0.03696571].\n",
      "Step : 36 time: --> 0.24341279999911786 s, odometry: - [2.78995324 0.20149654 0.02832955].\n",
      "Step : 37 time: --> 0.2449973879903555 s, odometry: - [2.92907074 0.20543873 0.01969539].\n",
      "Step : 38 time: --> 0.24448518601059913 s, odometry: - [3.06713868 0.20815839 0.00947697].\n",
      "Step : 39 time: --> 0.24515545699000357 s, odometry: - [ 3.20981349  0.20951055 -0.00328585].\n",
      "Step : 40 time: --> 0.24550450399518012 s, odometry: - [ 3.35554304  0.20903171 -0.01676063].\n",
      "Step : 41 time: --> 0.24617705500125886 s, odometry: - [ 3.50547748  0.20651848 -0.03094582].\n",
      "Step : 42 time: --> 0.24530203399062156 s, odometry: - [ 3.65747199  0.20181338 -0.04792092].\n",
      "Step : 43 time: --> 0.2443110560029745 s, odometry: - [ 3.80621775  0.19467988 -0.06310346].\n",
      "Step : 44 time: --> 0.24419877199828624 s, odometry: - [ 3.95591174  0.18522112 -0.07776581].\n",
      "Step : 45 time: --> 0.2439701499938965 s, odometry: - [ 4.10706599  0.17344273 -0.08906073].\n",
      "Step : 46 time: --> 0.24392264799773694 s, odometry: - [ 4.26519958  0.15932188 -0.09865691].\n",
      "Step : 47 time: --> 0.2442959880232811 s, odometry: - [ 4.42637123  0.1433694  -0.11478093].\n",
      "Step : 48 time: --> 0.24668315199017524 s, odometry: - [ 4.58458639  0.12512914 -0.13222513].\n",
      "Step : 49 time: --> 0.24503067499399186 s, odometry: - [ 4.73803438  0.10472038 -0.14790702].\n",
      "Step : 50 time: --> 0.24298373299837112 s, odometry: - [ 4.89646797  0.08111455 -0.16207722].\n",
      "Step : 51 time: --> 0.2436947440057993 s, odometry: - [ 5.06148222  0.05413282 -0.17610893].\n",
      "Step : 52 time: --> 0.24601147100329399 s, odometry: - [ 5.22903182  0.02431696 -0.19004128].\n",
      "Step : 53 time: --> 0.24429264299571515 s, odometry: - [ 5.39614248 -0.00782888 -0.20106986].\n",
      "Step : 54 time: --> 0.2528054460138083 s, odometry: - [ 5.56764742 -0.04278572 -0.2081629 ].\n",
      "Step : 55 time: --> 0.24666137398779392 s, odometry: - [ 5.73892222 -0.07896284 -0.21343376].\n",
      "Step : 56 time: --> 0.24775261601805687 s, odometry: - [ 5.90589007 -0.11515059 -0.22475928].\n",
      "Step : 57 time: --> 0.2457420479953289 s, odometry: - [ 6.07884784 -0.15469255 -0.2311872 ].\n",
      "Step : 58 time: --> 0.2478662900030613 s, odometry: - [ 6.25588811 -0.19636712 -0.23333188].\n",
      "Step : 59 time: --> 0.2470963450074196 s, odometry: - [ 6.43120445 -0.23803292 -0.23026988].\n",
      "Step : 60 time: --> 0.24450098100304604 s, odometry: - [ 6.61198589 -0.28041316 -0.2239376 ].\n",
      "Step : 61 time: --> 0.24472607199847699 s, odometry: - [ 6.79372498 -0.32180562 -0.21955294].\n",
      "Step : 62 time: --> 0.24557208600640296 s, odometry: - [ 6.97905056 -0.36316103 -0.21639012].\n",
      "Step : 63 time: --> 0.24433861500024795 s, odometry: - [ 7.16764508 -0.40462015 -0.21093449].\n",
      "Step : 64 time: --> 0.2453079719990492 s, odometry: - [ 7.35855809 -0.44549837 -0.20759176].\n",
      "Step : 65 time: --> 0.2449172569960356 s, odometry: - [ 7.55246419 -0.48634005 -0.19881461].\n",
      "Step : 66 time: --> 0.24501768399775029 s, odometry: - [ 7.74631399 -0.52539618 -0.18276322].\n",
      "Step : 67 time: --> 0.24590961599349975 s, odometry: - [ 7.93613726 -0.56048039 -0.17196124].\n",
      "Step : 68 time: --> 0.25619792099297045 s, odometry: - [ 8.126801   -0.59359421 -0.15753405].\n",
      "Step : 69 time: --> 0.24708876200020313 s, odometry: - [ 8.31711769 -0.62382607 -0.14155276].\n",
      "Step : 70 time: --> 0.2476780639886856 s, odometry: - [ 8.5116192  -0.65154367 -0.12730101].\n",
      "Step : 71 time: --> 0.2475328309983015 s, odometry: - [ 8.71199333 -0.67719019 -0.1144432 ].\n",
      "Step : 72 time: --> 0.24813172499835492 s, odometry: - [ 8.90625462 -0.69951964 -0.09222479].\n",
      "Step : 73 time: --> 0.24476510100066662 s, odometry: - [ 9.09612499 -0.71708021 -0.06791821].\n",
      "Step : 74 time: --> 0.24465120899677276 s, odometry: - [ 9.28565473 -0.72997257 -0.05167338].\n",
      "Step : 75 time: --> 0.24490258999168873 s, odometry: - [ 9.47489257 -0.73975984 -0.03598883].\n",
      "Step : 76 time: --> 0.2439705930054188 s, odometry: - [ 9.6680153  -0.7467131  -0.02403312].\n",
      "Step : 77 time: --> 0.24363455200195314 s, odometry: - [ 9.86229796e+00 -7.51383217e-01 -7.15090357e-03].\n",
      "Step : 78 time: --> 0.2438875270038843 s, odometry: - [ 1.00583851e+01 -7.52785441e-01  8.21037614e-03].\n",
      "Step : 79 time: --> 0.2433962370157242 s, odometry: - [10.25604355 -0.75116255  0.02001906].\n",
      "Step : 80 time: --> 0.24435189200937749 s, odometry: - [10.45474071 -0.74718429  0.03098354].\n",
      "Step : 81 time: --> 0.24446279199421406 s, odometry: - [10.6604796  -0.74080773  0.0447347 ].\n",
      "Step : 82 time: --> 0.2437289989888668 s, odometry: - [10.86298774 -0.73174254  0.06267768].\n",
      "Step : 83 time: --> 0.24502805697917937 s, odometry: - [11.06604514 -0.71899868  0.07261653].\n",
      "Step : 84 time: --> 0.2446164110004902 s, odometry: - [11.27183351 -0.70402872  0.08805224].\n",
      "Step : 85 time: --> 0.2438393050134182 s, odometry: - [11.48110923 -0.68555376  0.09945416].\n",
      "Step : 86 time: --> 0.24452480500936508 s, odometry: - [11.69102841 -0.66460731  0.10791591].\n",
      "Step : 87 time: --> 0.2436671089977026 s, odometry: - [11.90243426 -0.64170428  0.12045002].\n",
      "Step : 88 time: --> 0.24464159297943117 s, odometry: - [12.11293304 -0.61622637  0.13002477].\n",
      "Step : 89 time: --> 0.2464527239948511 s, odometry: - [12.32132171 -0.58897694  0.13555164].\n",
      "Step : 90 time: --> 0.24666271501779558 s, odometry: - [12.52878381 -0.5606816   0.14130992].\n",
      "Step : 91 time: --> 0.24622854600846766 s, odometry: - [12.7355534  -0.53126695  0.14750096].\n",
      "Step : 92 time: --> 0.2451982119977474 s, odometry: - [12.94096302 -0.50074718  0.15168729].\n",
      "Step : 93 time: --> 0.24486912100017072 s, odometry: - [13.14700288 -0.46925162  0.15540762].\n",
      "Step : 94 time: --> 0.24526097600162028 s, odometry: - [13.35597705 -0.43651144  0.15558345].\n",
      "Step : 95 time: --> 0.24536698299646378 s, odometry: - [13.5651471  -0.40370289  0.1572501 ].\n",
      "Step : 96 time: --> 0.24453148098289967 s, odometry: - [13.77258567 -0.3708116   0.16050018].\n",
      "Step : 97 time: --> 0.24268789100646973 s, odometry: - [13.98034023 -0.33717765  0.16441516].\n",
      "Step : 98 time: --> 0.2444608630090952 s, odometry: - [14.18783479 -0.30275164  0.17053773].\n",
      "Step : 99 time: --> 0.2437641209959984 s, odometry: - [14.39540157 -0.26700647  0.17609981].\n",
      "Step : 100 time: --> 0.2452085050046444 s, odometry: - [14.60321891 -0.23002682  0.17947246].\n",
      "Step : 101 time: --> 0.24387578600645066 s, odometry: - [14.8115694  -0.19222692  0.1825468 ].\n",
      "Step : 102 time: --> 0.24387904800474644 s, odometry: - [15.02043267 -0.15367037  0.18665017].\n",
      "Step : 103 time: --> 0.24412032900750638 s, odometry: - [15.22910495 -0.11426295  0.19136743].\n",
      "Step : 104 time: --> 0.24357094499468804 s, odometry: - [15.43861725 -0.07367241  0.19567813].\n",
      "Step : 105 time: --> 0.24582934600114822 s, odometry: - [15.64726233 -0.03231594  0.20039561].\n",
      "Step : 106 time: --> 0.24527678100764752 s, odometry: - [1.58568050e+01 1.02467735e-02 2.05971729e-01].\n",
      "Step : 107 time: --> 0.244415977999568 s, odometry: - [16.06610535  0.05397689  0.21200867].\n",
      "Step : 108 time: --> 0.2464887190014124 s, odometry: - [16.27482233  0.09890182  0.21659304].\n",
      "Step : 109 time: --> 0.24454332600533962 s, odometry: - [16.48319002  0.14475205  0.22273323].\n",
      "Step : 110 time: --> 0.24509666000306607 s, odometry: - [16.69147345  0.19192639  0.22950996].\n",
      "Step : 111 time: --> 0.24534319201111793 s, odometry: - [16.8988596   0.24037729  0.23597076].\n",
      "Step : 112 time: --> 0.24523830600082874 s, odometry: - [17.10676399  0.29036797  0.24275025].\n",
      "Step : 113 time: --> 0.24561241699755193 s, odometry: - [17.31544251  0.34204379  0.24805392].\n",
      "Step : 114 time: --> 0.24450281098484994 s, odometry: - [17.52158259  0.39425289  0.25339959].\n",
      "Step : 115 time: --> 0.24495660699903965 s, odometry: - [17.72790229  0.44768274  0.26077486].\n",
      "Step : 116 time: --> 0.24543673500418664 s, odometry: - [17.93753621  0.50362385  0.2687214 ].\n",
      "Step : 117 time: --> 0.24569840900599957 s, odometry: - [18.14710365  0.56133497  0.27573776].\n",
      "Step : 118 time: --> 0.24532089999318124 s, odometry: - [18.35508036  0.62018099  0.28300797].\n",
      "Step : 119 time: --> 0.24486138299107552 s, odometry: - [18.56355162  0.68080732  0.2910347 ].\n",
      "Step : 120 time: --> 0.24453644700348376 s, odometry: - [18.77244438  0.74337905  0.29826365].\n",
      "Step : 121 time: --> 0.24357159599661826 s, odometry: - [18.97975267  0.80711283  0.30641306].\n",
      "Step : 122 time: --> 0.24545923200249672 s, odometry: - [19.18673512  0.87259733  0.31592437].\n",
      "Step : 123 time: --> 0.24469956800341605 s, odometry: - [19.39161598  0.9395672   0.32544601].\n",
      "Step : 124 time: --> 0.2443730499893427 s, odometry: - [19.59648384  1.00869873  0.33675069].\n",
      "Step : 125 time: --> 0.24419241300225258 s, odometry: - [19.80091124  1.08026573  0.34911917].\n",
      "Step : 126 time: --> 0.2453177070170641 s, odometry: - [20.00482555  1.15449678  0.36015133].\n",
      "Step : 127 time: --> 0.2448849810063839 s, odometry: - [20.20826471  1.23110701  0.37065002].\n",
      "Step : 128 time: --> 0.24441424199938774 s, odometry: - [20.41103197  1.30990463  0.38103747].\n",
      "Step : 129 time: --> 0.24450924499332904 s, odometry: - [20.61332519  1.39094657  0.39214008].\n",
      "Step : 130 time: --> 0.24538847701251507 s, odometry: - [20.81487159  1.47429786  0.40369649].\n",
      "Step : 131 time: --> 0.24593602600693704 s, odometry: - [21.01587962  1.56015991  0.41616776].\n",
      "Step : 132 time: --> 0.24415534698963165 s, odometry: - [21.21560228  1.6484341   0.42904187].\n",
      "Step : 133 time: --> 0.24541598801314832 s, odometry: - [21.41492722  1.73961766  0.44219589].\n",
      "Step : 134 time: --> 0.24383189699053764 s, odometry: - [21.61289103  1.83334677  0.45470504].\n",
      "Step : 135 time: --> 0.24458146099746228 s, odometry: - [21.80948603  1.92945642  0.46742551].\n",
      "Step : 136 time: --> 0.24512574499845505 s, odometry: - [22.00392917  2.02759797  0.48147857].\n",
      "Step : 137 time: --> 0.24337618701159955 s, odometry: - [22.19769516  2.12883907  0.49548547].\n",
      "Step : 138 time: --> 0.2454475750029087 s, odometry: - [22.38970743  2.23261306  0.50985435].\n",
      "Step : 139 time: --> 0.24508925598859788 s, odometry: - [22.58008666  2.33906694  0.52387368].\n",
      "Step : 140 time: --> 0.2471836760044098 s, odometry: - [22.76787752  2.44755689  0.53817334].\n",
      "Step : 141 time: --> 0.24356804399192333 s, odometry: - [22.95481095  2.55914667  0.55293695].\n",
      "Step : 142 time: --> 0.24565894198417665 s, odometry: - [23.14225385  2.67482771  0.56700401].\n",
      "Step : 143 time: --> 0.2455193869918585 s, odometry: - [23.32769178  2.79290526  0.58184254].\n",
      "Step : 144 time: --> 0.2440742339938879 s, odometry: - [23.51124168  2.91364532  0.59685053].\n",
      "Step : 145 time: --> 0.2438239450007677 s, odometry: - [23.69203636  3.0364995   0.61201028].\n",
      "Step : 146 time: --> 0.2456476819962263 s, odometry: - [23.87093869  3.16207379  0.62727296].\n",
      "Step : 147 time: --> 0.24438466200232506 s, odometry: - [24.04676884  3.2895412   0.64209882].\n",
      "Step : 148 time: --> 0.2447174329906702 s, odometry: - [24.22088088  3.41974414  0.65636682].\n",
      "Step : 149 time: --> 0.24504453100264073 s, odometry: - [24.39331686  3.55257151  0.67077625].\n",
      "Step : 150 time: --> 0.24513521400094032 s, odometry: - [24.56363176  3.68771952  0.68580638].\n",
      "Step : 151 time: --> 0.24577761499583722 s, odometry: - [24.73230325  3.82574511  0.70002976].\n",
      "Step : 152 time: --> 0.2447520609945059 s, odometry: - [24.89922348  3.96634858  0.71553384].\n",
      "Step : 153 time: --> 0.24524028497934341 s, odometry: - [25.06390154  4.10948624  0.73070241].\n",
      "Step : 154 time: --> 0.24601157899200915 s, odometry: - [25.22620931  4.25494376  0.74462451].\n",
      "Step : 155 time: --> 0.24640624399483205 s, odometry: - [25.38604645  4.40225057  0.75883997].\n",
      "Step : 156 time: --> 0.24448986200988293 s, odometry: - [25.54543418  4.55338934  0.77403365].\n",
      "Step : 157 time: --> 0.244569064989686 s, odometry: - [25.70279673  4.70721522  0.78865147].\n",
      "Step : 158 time: --> 0.24337041299045087 s, odometry: - [25.85770763  4.86313737  0.80379684].\n",
      "Step : 159 time: --> 0.24570543700456618 s, odometry: - [26.00973129  5.0208606   0.81846157].\n",
      "Step : 160 time: --> 0.24335102799534797 s, odometry: - [26.15908559  5.18043279  0.83258136].\n",
      "Step : 161 time: --> 0.2452049600034952 s, odometry: - [26.3053879   5.34123608  0.84782639].\n",
      "Step : 162 time: --> 0.2443780239969492 s, odometry: - [26.44976639  5.50486814  0.86431076].\n",
      "Step : 163 time: --> 0.24536560498178006 s, odometry: - [26.59149021  5.67093073  0.8799884 ].\n",
      "Step : 164 time: --> 0.24360283300280572 s, odometry: - [26.73050031  5.83908229  0.89669975].\n",
      "Step : 165 time: --> 0.24449087700247765 s, odometry: - [26.86749266  6.01054912  0.91385304].\n",
      "Step : 166 time: --> 0.24498847000300883 s, odometry: - [27.00201899  6.18498258  0.93084814].\n",
      "Step : 167 time: --> 0.24384697100520134 s, odometry: - [27.13265718  6.36046226  0.94825126].\n",
      "Step : 168 time: --> 0.24523103299736976 s, odometry: - [27.26006903  6.53797588  0.9655965 ].\n",
      "Step : 169 time: --> 0.2450084490031004 s, odometry: - [27.38411393  6.71728393  0.9816572 ].\n",
      "Step : 170 time: --> 0.24360755698382855 s, odometry: - [27.50610165  6.89981569  0.99719736].\n",
      "Step : 171 time: --> 0.24478676798939705 s, odometry: - [27.62607184  7.08551142  1.01185483].\n",
      "Step : 172 time: --> 0.24524172700941563 s, odometry: - [27.742944    7.27236458  1.02706931].\n",
      "Step : 173 time: --> 0.24541875199973584 s, odometry: - [27.85680592  7.46071953  1.04341235].\n",
      "Step : 174 time: --> 0.24396526899933815 s, odometry: - [27.96739973  7.65061005  1.06027998].\n",
      "Step : 175 time: --> 0.25667856200039385 s, odometry: - [28.07435239  7.8415844   1.07663988].\n",
      "Step : 176 time: --> 0.24766304701566697 s, odometry: - [28.17842361  8.03475997  1.09345572].\n",
      "Step : 177 time: --> 0.2439661980122328 s, odometry: - [28.27990695  8.23096338  1.10897566].\n",
      "Step : 178 time: --> 0.243688069999218 s, odometry: - [28.3783899   8.42883221  1.12445488].\n",
      "Step : 179 time: --> 0.2434030600041151 s, odometry: - [28.47410825  8.62884935  1.14079934].\n",
      "Step : 180 time: --> 0.24462105798721315 s, odometry: - [28.5660738   8.82937717  1.15762332].\n",
      "Step : 181 time: --> 0.25105567298829556 s, odometry: - [28.6545086   9.03109483  1.17464364].\n",
      "Step : 182 time: --> 0.2466219619959593 s, odometry: - [28.73904738  9.23321233  1.19124714].\n",
      "Step : 183 time: --> 0.24495195700228214 s, odometry: - [28.8206148   9.43769828  1.20811895].\n",
      "Step : 184 time: --> 0.24633450599014758 s, odometry: - [28.8981643   9.6420649   1.22299206].\n",
      "Step : 185 time: --> 0.2452572930008173 s, odometry: - [28.97272239  9.84771848  1.23794313].\n",
      "Step : 186 time: --> 0.2477090680003166 s, odometry: - [29.04451489 10.05538172  1.25223514].\n",
      "Step : 187 time: --> 0.2464483100026846 s, odometry: - [29.11273228 10.26223064  1.26595992].\n",
      "Step : 188 time: --> 0.24541978199779987 s, odometry: - [29.17776066 10.46890388  1.28103348].\n",
      "Step : 189 time: --> 0.2441434800028801 s, odometry: - [29.23947468 10.67589059  1.29530713].\n",
      "Step : 190 time: --> 0.24439997000992297 s, odometry: - [29.29804917 10.88310419  1.30919562].\n",
      "Step : 191 time: --> 0.2441000270098448 s, odometry: - [29.35390323 11.09172018  1.32354383].\n",
      "Step : 192 time: --> 0.24544979199767114 s, odometry: - [29.40687827 11.301591    1.33778735].\n",
      "Step : 193 time: --> 0.24736195600032806 s, odometry: - [29.45705885 11.51303832  1.35184182].\n",
      "Step : 194 time: --> 0.25084765200316905 s, odometry: - [29.50455897 11.72650099  1.36645195].\n",
      "Step : 195 time: --> 0.24443720699846744 s, odometry: - [29.54874887 11.93973468  1.38083595].\n",
      "Step : 196 time: --> 0.2539099129885435 s, odometry: - [29.58950353 12.15169084  1.3956205 ].\n",
      "Step : 197 time: --> 0.2498456070125103 s, odometry: - [29.62724064 12.36490692  1.40967811].\n",
      "Step : 198 time: --> 0.24588392201066017 s, odometry: - [29.66207869 12.57925935  1.4229248 ].\n",
      "Step : 199 time: --> 0.24516872799396514 s, odometry: - [29.69409228 12.79417504  1.43716645].\n",
      "Step : 200 time: --> 0.2447130379974842 s, odometry: - [29.72311472 13.01006598  1.4519705 ].\n",
      "Step : 201 time: --> 0.24311342500150204 s, odometry: - [29.74866928 13.22411179  1.46586577].\n",
      "Step : 202 time: --> 0.2413515159934759 s, odometry: - [29.77124302 13.43845195  1.47984037].\n",
      "Step : 203 time: --> 0.24094553799927235 s, odometry: - [29.79097055 13.65474455  1.49453307].\n",
      "Step : 204 time: --> 0.24141525200009345 s, odometry: - [29.80748652 13.87088981  1.50887483].\n",
      "Step : 205 time: --> 0.24081943899393082 s, odometry: - [29.82094616 14.08797797  1.52301079].\n",
      "Step : 206 time: --> 0.24139417101442814 s, odometry: - [29.83129764 14.30443683  1.53613908].\n",
      "Step : 207 time: --> 0.24204874600470067 s, odometry: - [29.83880677 14.52101865  1.54971673].\n",
      "Step : 208 time: --> 0.24197304299473762 s, odometry: - [29.84341562 14.73962613  1.564032  ].\n",
      "Step : 209 time: --> 0.2418735300153494 s, odometry: - [29.84490486 14.95978409  1.57811717].\n",
      "Step : 210 time: --> 0.24094853399693966 s, odometry: - [29.84330007 15.17898794  1.59223814].\n",
      "Step : 211 time: --> 0.24176875400543213 s, odometry: - [29.83858058 15.39906137  1.60737376].\n",
      "Step : 212 time: --> 0.24134215499460698 s, odometry: - [29.83059303 15.61733743  1.621414  ].\n",
      "Step : 213 time: --> 0.2423870840072632 s, odometry: - [29.81948853 15.83652996  1.63441374].\n",
      "Step : 214 time: --> 0.24242836497724057 s, odometry: - [29.80553388 16.05558662  1.64855373].\n",
      "Step : 215 time: --> 0.24200910899043082 s, odometry: - [29.7885175  16.27398484  1.66229609].\n",
      "Step : 216 time: --> 0.24168515598773957 s, odometry: - [29.7683737  16.49352142  1.67703616].\n",
      "Step : 217 time: --> 0.24158901900053023 s, odometry: - [29.74500714 16.71263496  1.69309123].\n",
      "Step : 218 time: --> 0.2414210710078478 s, odometry: - [29.71822773 16.93051627  1.70694301].\n",
      "Step : 219 time: --> 0.24211915799975395 s, odometry: - [29.68842573 17.14805835  1.72230157].\n",
      "Step : 220 time: --> 0.24230445800721645 s, odometry: - [29.65538786 17.36445152  1.73657296].\n",
      "Step : 221 time: --> 0.24171080899238587 s, odometry: - [29.61942143 17.57941761  1.75092866].\n",
      "Step : 222 time: --> 0.24100530199706555 s, odometry: - [29.57998295 17.79598612  1.76555881].\n",
      "Step : 223 time: --> 0.24235211700201034 s, odometry: - [29.53732191 18.01225086  1.78130442].\n",
      "Step : 224 time: --> 0.24080315901339053 s, odometry: - [29.49125607 18.22784052  1.79551809].\n",
      "Step : 225 time: --> 0.24095602901279925 s, odometry: - [29.44232048 18.4419233   1.81127587].\n",
      "Step : 226 time: --> 0.24103205600380898 s, odometry: - [29.39032989 18.65393508  1.82672159].\n",
      "Step : 227 time: --> 0.2413985710144043 s, odometry: - [29.33494524 18.86559901  1.84080775].\n",
      "Step : 228 time: --> 0.24115131199359893 s, odometry: - [29.27626865 19.07760354  1.85399009].\n",
      "Step : 229 time: --> 0.2418075630068779 s, odometry: - [29.2150915  19.28782319  1.86827165].\n",
      "Step : 230 time: --> 0.2422520809918642 s, odometry: - [29.15077322 19.49762137  1.88291461].\n",
      "Step : 231 time: --> 0.24154759600758552 s, odometry: - [29.08322483 19.70696683  1.89601171].\n",
      "Step : 232 time: --> 0.2471333020031452 s, odometry: - [29.01281958 19.91576825  1.91077234].\n",
      "Step : 233 time: --> 0.2469031310081482 s, odometry: - [28.94003328 20.1215479   1.92431014].\n",
      "Step : 234 time: --> 0.24849569900333882 s, odometry: - [28.86422644 20.32697777  1.93798091].\n",
      "Step : 235 time: --> 0.24880458299815655 s, odometry: - [28.78585853 20.53072782  1.95319657].\n",
      "Step : 236 time: --> 0.24896252299845217 s, odometry: - [28.70498806 20.73179882  1.96801531].\n",
      "Step : 237 time: --> 0.24712355299293995 s, odometry: - [28.62050461 20.93318055  1.98299564].\n",
      "Step : 238 time: --> 0.24802545298635958 s, odometry: - [28.53287595 21.13358986  1.99882211].\n",
      "Step : 239 time: --> 0.24693473500013352 s, odometry: - [28.4424676  21.33175222  2.01245864].\n",
      "Step : 240 time: --> 0.24936503300070761 s, odometry: - [28.34884329 21.52976778  2.02740774].\n",
      "Step : 241 time: --> 0.2490503460019827 s, odometry: - [28.2520369  21.72683498  2.04227453].\n",
      "Step : 242 time: --> 0.24633297298848628 s, odometry: - [28.15280988 21.92146381  2.05685334].\n",
      "Step : 243 time: --> 0.24697304199635983 s, odometry: - [28.05008953 22.11588696  2.07170295].\n",
      "Step : 244 time: --> 0.24809935499727725 s, odometry: - [27.94417855 22.30933863  2.0871035 ].\n",
      "Step : 245 time: --> 0.24663647799193858 s, odometry: - [27.83509343 22.50150198  2.10175364].\n",
      "Step : 246 time: --> 0.24701243099570275 s, odometry: - [27.72295751 22.69246795  2.1162733 ].\n",
      "Step : 247 time: --> 0.2516195020079613 s, odometry: - [27.60937167 22.87962563  2.13128553].\n",
      "Step : 248 time: --> 0.253507081001997 s, odometry: - [27.49263354 23.06562359  2.14719769].\n",
      "Step : 249 time: --> 0.24658822500705718 s, odometry: - [27.37244088 23.2505248   2.16283809].\n",
      "Step : 250 time: --> 0.2510066080093384 s, odometry: - [27.25022352 23.43225612  2.1778351 ].\n",
      "Step : 251 time: --> 0.24969591000676156 s, odometry: - [27.12542055 23.61195278  2.19192286].\n",
      "Step : 252 time: --> 0.24582424999773503 s, odometry: - [26.99803183 23.78996669  2.20638034].\n",
      "Step : 253 time: --> 0.24906187500059604 s, odometry: - [26.8691897  23.96461997  2.22151009].\n",
      "Step : 254 time: --> 0.25464633299410344 s, odometry: - [26.73768336 24.13735207  2.23678491].\n",
      "Step : 255 time: --> 0.25111313900351523 s, odometry: - [26.60311195 24.30861796  2.25099573].\n",
      "Step : 256 time: --> 0.24918501101434232 s, odometry: - [26.46600714 24.47809422  2.26600763].\n",
      "Step : 257 time: --> 0.24521533200144768 s, odometry: - [26.325748   24.64624339  2.27993684].\n",
      "Step : 258 time: --> 0.24401543998718261 s, odometry: - [26.18248261 24.8132125   2.29465753].\n",
      "Step : 259 time: --> 0.24309358102083206 s, odometry: - [26.03566084 24.97931502  2.30903113].\n",
      "Step : 260 time: --> 0.2454724099934101 s, odometry: - [25.88558831 25.14425566  2.32361913].\n",
      "Step : 261 time: --> 0.2471144299954176 s, odometry: - [25.73341575 25.30667995  2.3383464 ].\n",
      "Step : 262 time: --> 0.25070017601549627 s, odometry: - [25.57838861 25.46734213  2.35482804].\n",
      "Step : 263 time: --> 0.24795704399049281 s, odometry: - [25.42260788 25.62354919  2.37076602].\n",
      "Step : 264 time: --> 0.24386152099072933 s, odometry: - [25.26408529 25.77751797  2.38671744].\n",
      "Step : 265 time: --> 0.24448296700417996 s, odometry: - [25.10301461 25.92904431  2.40243253].\n",
      "Step : 266 time: --> 0.24593462000787258 s, odometry: - [24.94050258 26.07718224  2.41732833].\n",
      "Step : 267 time: --> 0.24468695598840715 s, odometry: - [24.77570235 26.22297127  2.43329334].\n",
      "Step : 268 time: --> 0.24408999100327491 s, odometry: - [24.60865966 26.36605601  2.4494695 ].\n",
      "Step : 269 time: --> 0.2449511640071869 s, odometry: - [24.43890242 26.50676978  2.4663451 ].\n",
      "Step : 270 time: --> 0.24764045099914073 s, odometry: - [24.26782706 26.64377226  2.48222351].\n",
      "Step : 271 time: --> 0.24796238999068737 s, odometry: - [24.0950313  26.77770532  2.49721084].\n",
      "Step : 272 time: --> 0.2457386509925127 s, odometry: - [23.92003991 26.90918983  2.5109195 ].\n",
      "Step : 273 time: --> 0.24730838598310947 s, odometry: - [23.74142991 27.03960125  2.52571679].\n",
      "Step : 274 time: --> 0.24620287899672985 s, odometry: - [23.56017536 27.16787531  2.53997185].\n",
      "Step : 275 time: --> 0.24297205601632596 s, odometry: - [23.37650492 27.29396852  2.55467471].\n",
      "Step : 276 time: --> 0.2432915199995041 s, odometry: - [23.1897878  27.41815428  2.57089202].\n",
      "Step : 277 time: --> 0.24454941599071026 s, odometry: - [23.00193676 27.53874666  2.58510766].\n",
      "Step : 278 time: --> 0.24599956499040126 s, odometry: - [22.81214575 27.65680875  2.60005238].\n",
      "Step : 279 time: --> 0.2437084150016308 s, odometry: - [22.62131273 27.77159963  2.61534878].\n",
      "Step : 280 time: --> 0.24381358300149442 s, odometry: - [22.42921306 27.88318696  2.63089919].\n",
      "Step : 281 time: --> 0.24433351700007916 s, odometry: - [22.23588816 27.99150101  2.64525853].\n",
      "Step : 282 time: --> 0.24266087399423122 s, odometry: - [22.04383321 28.09550876  2.65794281].\n",
      "Step : 283 time: --> 0.24413747499883176 s, odometry: - [21.85016086 28.19723686  2.66998433].\n",
      "Step : 284 time: --> 0.24464295500516892 s, odometry: - [21.65594214 28.29628664  2.68234059].\n",
      "Step : 285 time: --> 0.24379634201526643 s, odometry: - [21.4618477  28.39226975  2.69545051].\n",
      "Step : 286 time: --> 0.2432888220101595 s, odometry: - [21.26728923 28.4853282   2.70594862].\n",
      "Step : 287 time: --> 0.245501428976655 s, odometry: - [21.07354373 28.57551092  2.71594377].\n",
      "Step : 288 time: --> 0.2442853619903326 s, odometry: - [20.87865873 28.66386499  2.72498844].\n",
      "Step : 289 time: --> 0.24320058301091194 s, odometry: - [20.68451542 28.74977451  2.73430611].\n",
      "Step : 290 time: --> 0.24730595099925995 s, odometry: - [20.48632489 28.83527568  2.74516222].\n",
      "Step : 291 time: --> 0.24850955000519753 s, odometry: - [20.28506453 28.91952163  2.75919623].\n",
      "Step : 292 time: --> 0.2479181939959526 s, odometry: - [20.08110872 29.00155146  2.7756777 ].\n",
      "Step : 293 time: --> 0.2509973350018263 s, odometry: - [19.87775529 29.07947059  2.79161033].\n",
      "Step : 294 time: --> 0.2486153979897499 s, odometry: - [19.67522467 29.15339598  2.80657443].\n",
      "Step : 295 time: --> 0.2509488810002804 s, odometry: - [19.47193573 29.22416931  2.82175968].\n",
      "Step : 296 time: --> 0.24903483401238918 s, odometry: - [19.27048695 29.29088996  2.83656811].\n",
      "Step : 297 time: --> 0.2457530979961157 s, odometry: - [19.06881578 29.35438617  2.85201821].\n",
      "Step : 298 time: --> 0.24519442801177502 s, odometry: - [18.86667111 29.41461505  2.86770682].\n",
      "Step : 299 time: --> 0.24592052498459815 s, odometry: - [18.66370223 29.47163837  2.88454131].\n",
      "Step : 300 time: --> 0.2510554990023375 s, odometry: - [18.46175327 29.52472403  2.90207095].\n",
      "Step : 301 time: --> 0.2494674960076809 s, odometry: - [18.25870431 29.57431058  2.91890633].\n",
      "Step : 302 time: --> 0.2515229059904814 s, odometry: - [18.0563504  29.62013196  2.93752831].\n",
      "Step : 303 time: --> 0.2501495059877634 s, odometry: - [17.8545906  29.66188512  2.9568119 ].\n",
      "Step : 304 time: --> 0.2612555269896984 s, odometry: - [17.6481791  29.7004661   2.97615414].\n",
      "Step : 305 time: --> 0.24493159098923206 s, odometry: - [17.43821179 29.7355232   2.99604707].\n",
      "Step : 306 time: --> 0.24977635100483894 s, odometry: - [17.22872    29.76623094  3.02018485].\n",
      "Step : 307 time: --> 0.2410436390042305 s, odometry: - [17.02220144 29.79142783  3.04271325].\n",
      "Step : 308 time: --> 0.24457780000567436 s, odometry: - [16.82309413 29.81117985  3.06640289].\n",
      "Step : 309 time: --> 0.2459049530029297 s, odometry: - [16.61741495 29.82667403  3.09080876].\n",
      "Step : 310 time: --> 0.24910166800022127 s, odometry: - [16.40949601 29.83724205  3.11266246].\n",
      "Step : 311 time: --> 0.24294595201313496 s, odometry: - [16.20313286 29.84321384  3.13585776].\n",
      "Step : 312 time: --> 0.2432007170021534 s, odometry: - [16.00112647 29.84437234  3.15361706].\n",
      "Step : 313 time: --> 0.2421871959865093 s, odometry: - [15.8012203  29.84196848  3.17275895].\n",
      "Step : 314 time: --> 0.24203447701036931 s, odometry: - [15.6006628  29.83571582  3.18937961].\n",
      "Step : 315 time: --> 0.24199432900547982 s, odometry: - [15.40450428 29.82633485  3.20395231].\n",
      "Step : 316 time: --> 0.24202858600020408 s, odometry: - [15.20641855 29.81396626  3.2190444 ].\n",
      "Step : 317 time: --> 0.2462598530203104 s, odometry: - [15.00096402 29.79802155  3.22978174].\n",
      "Step : 318 time: --> 0.24381149600446225 s, odometry: - [14.79057196 29.77941902  3.24182558].\n",
      "Step : 319 time: --> 0.2487533740103245 s, odometry: - [14.58217711 29.75846076  3.25475974].\n",
      "Step : 320 time: --> 0.2471212719976902 s, odometry: - [14.37237468 29.73461615  3.26386008].\n",
      "Step : 321 time: --> 0.24215004101395607 s, odometry: - [14.16110997 29.70865587  3.26998478].\n",
      "Step : 322 time: --> 0.24256731298565865 s, odometry: - [13.95094707 29.68152335  3.27712762].\n",
      "Step : 323 time: --> 0.24726316100358964 s, odometry: - [13.73213898 29.65168427  3.27888322].\n",
      "Step : 324 time: --> 0.24925713001191616 s, odometry: - [13.51190764 29.62125717  3.2861936 ].\n",
      "Step : 325 time: --> 0.24531857600808143 s, odometry: - [13.28905059 29.58880533  3.28773715].\n",
      "Step : 326 time: --> 0.26309833499789237 s, odometry: - [13.07154579 29.55678995  3.28712486].\n",
      "Step : 327 time: --> 0.2446565999984741 s, odometry: - [12.85512481 29.52506947  3.28577303].\n",
      "Step : 328 time: --> 0.24398732599616052 s, odometry: - [12.64208009 29.49413796  3.28133289].\n",
      "Step : 329 time: --> 0.2439913409948349 s, odometry: - [12.42796985 29.46402186  3.27349899].\n",
      "Step : 330 time: --> 0.24404363799095155 s, odometry: - [12.2154912  29.43583089  3.26397022].\n",
      "Step : 331 time: --> 0.24537623700499533 s, odometry: - [11.99527396 29.4087459   3.25634169].\n",
      "Step : 332 time: --> 0.24646433900296688 s, odometry: - [11.77801208 29.38370531  3.24491537].\n",
      "Step : 333 time: --> 0.24565336599946022 s, odometry: - [11.56426054 29.36154099  3.24343961].\n",
      "Step : 334 time: --> 0.24397771300375462 s, odometry: - [11.35183241 29.33983071  3.23621237].\n",
      "Step : 335 time: --> 0.2432608550041914 s, odometry: - [11.13965368 29.31969429  3.2269706 ].\n",
      "Step : 336 time: --> 0.24051707500219346 s, odometry: - [10.92356078 29.30119976  3.20287942].\n",
      "Step : 337 time: --> 0.2449603189975023 s, odometry: - [10.70148477 29.28757238  3.18460854].\n",
      "Step : 338 time: --> 0.25057195499539375 s, odometry: - [10.48355997 29.27819236  3.15828663].\n",
      "Step : 339 time: --> 0.2493473080098629 s, odometry: - [10.26332805 29.27451548  3.14067253].\n",
      "Step : 340 time: --> 0.2491336399912834 s, odometry: - [10.04099565 29.27472005  3.12715087].\n",
      "Step : 341 time: --> 0.25108165898919105 s, odometry: - [ 9.8207512  29.27790099  3.11285959].\n",
      "Step : 342 time: --> 0.2517788810133934 s, odometry: - [ 9.60128067 29.28420879  3.10050881].\n",
      "Step : 343 time: --> 0.26863834500312805 s, odometry: - [ 9.37769858 29.29339957  3.08366431].\n",
      "Step : 344 time: --> 0.25996103501319884 s, odometry: - [ 9.15642415 29.30623199  3.07026232].\n",
      "Step : 345 time: --> 0.24387226298451423 s, odometry: - [ 8.93733668 29.32188613  3.06070027].\n",
      "Step : 346 time: --> 0.242703208014369 s, odometry: - [ 8.71688251 29.3397582   3.05452163].\n",
      "Step : 347 time: --> 0.24120198099315165 s, odometry: - [ 8.49732838 29.35892346  3.04458375].\n",
      "Step : 348 time: --> 0.24159274299442768 s, odometry: - [ 8.2779009  29.3802769   3.03805762].\n",
      "Step : 349 time: --> 0.24212543199956418 s, odometry: - [ 8.06126897 29.40278638  3.03454791].\n",
      "Step : 350 time: --> 0.2424250189960003 s, odometry: - [ 7.84282788 29.42625908  3.03541904].\n",
      "Step : 351 time: --> 0.2439914240092039 s, odometry: - [ 7.62343232 29.44964102  3.03477554].\n",
      "Step : 352 time: --> 0.24361999897658826 s, odometry: - [ 7.4018882  29.47339614  3.03576771].\n",
      "Step : 353 time: --> 0.2416787959933281 s, odometry: - [ 7.17899619 29.49707213  3.03603687].\n",
      "Step : 354 time: --> 0.2420637180060148 s, odometry: - [ 6.95717345 29.52057415  3.03617966].\n",
      "Step : 355 time: --> 0.24459501402080058 s, odometry: - [ 6.73530706 29.54404876  3.03785842].\n",
      "Step : 356 time: --> 0.24965113100409508 s, odometry: - [ 6.51436695 29.56705038  3.03900294].\n",
      "Step : 357 time: --> 0.24937362299859525 s, odometry: - [ 6.29466789 29.58966865  3.04312163].\n",
      "Step : 358 time: --> 0.24299605000019073 s, odometry: - [ 6.07547079 29.61132325  3.04625649].\n",
      "Step : 359 time: --> 0.2413247420042753 s, odometry: - [ 5.85467352 29.63243722  3.04756825].\n",
      "Step : 360 time: --> 0.2417423759996891 s, odometry: - [ 5.63269246 29.65337058  3.04911513].\n",
      "Step : 361 time: --> 0.24222261700034142 s, odometry: - [ 5.41112748 29.67391897  3.050557  ].\n",
      "Step : 362 time: --> 0.242159363001585 s, odometry: - [ 5.19117401 29.69399808  3.0525494 ].\n",
      "Step : 363 time: --> 0.24334467300772666 s, odometry: - [ 4.97305729 29.7134714   3.05582844].\n",
      "Step : 364 time: --> 0.24186146099865435 s, odometry: - [ 4.75523539 29.73219866  3.05997965].\n",
      "Step : 365 time: --> 0.24240021900832653 s, odometry: - [ 4.53828361 29.74994416  3.06403165].\n",
      "Step : 366 time: --> 0.24142775000631808 s, odometry: - [ 4.32146997 29.76679425  3.0685498 ].\n",
      "Step : 367 time: --> 0.24190441799163817 s, odometry: - [ 4.10416443 29.78269515  3.07223553].\n",
      "Step : 368 time: --> 0.24256497700512408 s, odometry: - [ 3.88496376 29.7979227   3.07579916].\n",
      "Step : 369 time: --> 0.24350491800904275 s, odometry: - [ 3.66740674 29.81225723  3.07986029].\n",
      "Step : 370 time: --> 0.2407584989964962 s, odometry: - [ 3.45014048 29.82568665  3.08243893].\n",
      "Step : 371 time: --> 0.24155286699533463 s, odometry: - [ 3.23313349 29.83853842  3.08482595].\n",
      "Step : 372 time: --> 0.2409982559978962 s, odometry: - [ 3.01626912 29.85086234  3.08832675].\n",
      "Step : 373 time: --> 0.248518796980381 s, odometry: - [ 2.80004258 29.86239074  3.09256227].\n",
      "Step : 374 time: --> 0.24737109398841858 s, odometry: - [ 2.5835266  29.87301512  3.09603271].\n",
      "Step : 375 time: --> 0.24538272701203823 s, odometry: - [ 2.36570377 29.88294599  3.0970571 ].\n",
      "Step : 376 time: --> 0.24571917301416396 s, odometry: - [ 2.1476608  29.89266308  3.09996388].\n",
      "Step : 377 time: --> 0.2613381589949131 s, odometry: - [ 1.92936405 29.90175576  3.10464645].\n",
      "Step : 378 time: --> 0.25334595400094984 s, odometry: - [ 1.70988735 29.90986828  3.10883312].\n",
      "Step : 379 time: --> 0.250107671007514 s, odometry: - [ 1.48838547 29.91712717  3.1115908 ].\n",
      "Step : 380 time: --> 0.25442107900977134 s, odometry: - [ 1.2674251  29.92375838  3.1143239 ].\n",
      "Step : 381 time: --> 0.25104536800086497 s, odometry: - [ 1.04669293 29.92977897  3.11658746].\n",
      "Step : 382 time: --> 0.2602816859930754 s, odometry: - [ 0.82489411 29.93532625  3.11905804].\n",
      "Step : 383 time: --> 0.2600839500129223 s, odometry: - [ 0.6029582  29.94032833  3.1214234 ].\n",
      "Step : 384 time: --> 0.2676580329835415 s, odometry: - [ 0.38029622 29.94481987  3.12350324].\n",
      "Step : 385 time: --> 0.27274711000919344 s, odometry: - [ 0.15768775 29.94884716  3.12540401].\n",
      "Step : 386 time: --> 0.24672554498910904 s, odometry: - [-0.06456015 29.95244537  3.12640018].\n",
      "Step : 387 time: --> 0.24802630001306533 s, odometry: - [-0.28793704 29.95583928  3.1273315 ].\n",
      "Step : 388 time: --> 0.24797535100579263 s, odometry: - [-0.51002823 29.95900677  3.12826559].\n",
      "Step : 389 time: --> 0.248231546998024 s, odometry: - [-0.73211412 29.9619667   3.13012818].\n",
      "Step : 390 time: --> 0.24845771399140357 s, odometry: - [-0.95497501 29.96452179  3.13342805].\n",
      "Step : 391 time: --> 0.25250550399720667 s, odometry: - [-1.17672895 29.96633236  3.13583665].\n",
      "Step : 392 time: --> 0.25983303600549695 s, odometry: - [-1.39998156 29.96761742  3.13762637].\n",
      "Step : 393 time: --> 0.2570298179835081 s, odometry: - [-1.6236589  29.96850459  3.13742063].\n",
      "Step : 394 time: --> 0.2628089089989662 s, odometry: - [-1.84670071 29.96943514  3.13814442].\n",
      "Step : 395 time: --> 0.25176738801598547 s, odometry: - [-2.07007433 29.97020538  3.13837632].\n",
      "Step : 396 time: --> 0.2426665610074997 s, odometry: - [-2.29284054 29.97092188  3.13985411].\n",
      "Step : 397 time: --> 0.24186465400457383 s, odometry: - [-2.51542827 29.97130886  3.13946641].\n",
      "Step : 398 time: --> 0.24246847800910473 s, odometry: - [-2.73644967 29.9717788   3.14043457].\n",
      "Step : 399 time: --> 0.24112878799438475 s, odometry: - [-2.95725317 29.97203451  3.14183653].\n",
      "Step : 400 time: --> 0.2404467779994011 s, odometry: - [-3.17723099 29.97198086  3.14149081].\n",
      "Step : 401 time: --> 0.242333462998271 s, odometry: - [-3.39683417 29.97200323  3.14253384].\n",
      "Step : 402 time: --> 0.24202053000032903 s, odometry: - [-3.61671564 29.97179628  3.14462644].\n",
      "Step : 403 time: --> 0.24196323800086975 s, odometry: - [-3.83629543 29.97113012  3.14542865].\n",
      "Step : 404 time: --> 0.24273899999260903 s, odometry: - [-4.05563921 29.97028871  3.14692282].\n",
      "Step : 405 time: --> 0.24313645400106906 s, odometry: - [-4.27674065 29.96911019  3.14774749].\n",
      "Step : 406 time: --> 0.2427837409824133 s, odometry: - [-4.50028442 29.9677343   3.14838922].\n",
      "Step : 407 time: --> 0.24625653800368308 s, odometry: - [-4.72348768 29.96621726  3.14921437].\n",
      "Step : 408 time: --> 0.2452263009995222 s, odometry: - [-4.94701988 29.96451353  3.14980793].\n",
      "Step : 409 time: --> 0.24312047702074052 s, odometry: - [-5.16993002 29.96268222  3.1503518 ].\n",
      "Step : 410 time: --> 0.2433848479986191 s, odometry: - [-5.39367037 29.9607224   3.15101793].\n",
      "Step : 411 time: --> 0.24348762699961662 s, odometry: - [-5.61613458 29.95862555  3.15141731].\n",
      "Step : 412 time: --> 0.24197055998444558 s, odometry: - [-5.83850392 29.95644078  3.15103253].\n",
      "Step : 413 time: --> 0.24320022600889207 s, odometry: - [-6.06170975 29.95433368  3.15077068].\n",
      "Step : 414 time: --> 0.24203493301570417 s, odometry: - [-6.28497949 29.95228444  3.14941483].\n",
      "Step : 415 time: --> 0.24266073900461196 s, odometry: - [-6.5079981  29.95053992  3.14784691].\n",
      "Step : 416 time: --> 0.2423311170041561 s, odometry: - [-6.72886709 29.94915853  3.14596217].\n",
      "Step : 417 time: --> 0.2424987539947033 s, odometry: - [-6.95051793 29.94819002  3.14478582].\n",
      "Step : 418 time: --> 0.24185110999643802 s, odometry: - [-7.17185839 29.94748324  3.14301727].\n",
      "Step : 419 time: --> 0.2421521820127964 s, odometry: - [-7.39323921 29.94716785  3.14169422].\n",
      "Step : 420 time: --> 0.24169404898583888 s, odometry: - [-7.61472532 29.94714536  3.13957631].\n",
      "Step : 421 time: --> 0.24176240299642085 s, odometry: - [-7.83754766 29.94759464  3.13824598].\n",
      "Step : 422 time: --> 0.24180759198963642 s, odometry: - [-8.05987936 29.94833872  3.13869066].\n",
      "Step : 423 time: --> 0.2424343159943819 s, odometry: - [-8.28212187 29.94898366  3.13849716].\n",
      "Step : 424 time: --> 0.2427335489988327 s, odometry: - [-8.50599824 29.94967668  3.13768915].\n",
      "Step : 425 time: --> 0.24324493500590325 s, odometry: - [-8.72881934 29.95054646  3.13857093].\n",
      "Step : 426 time: --> 0.24864847801625728 s, odometry: - [-8.95244998 29.95122222  3.14035184].\n",
      "Step : 427 time: --> 0.2537918699979782 s, odometry: - [-9.17591895 29.9514995   3.14121012].\n",
      "Step : 428 time: --> 0.24359193602204324 s, odometry: - [-9.39761219 29.9515843   3.14154666].\n",
      "Step : 429 time: --> 0.24184322801232339 s, odometry: - [-9.61950195 29.95159451  3.14216655].\n",
      "Step : 430 time: --> 0.24325874100625516 s, odometry: - [-9.84363464 29.95146588  3.14315802].\n",
      "Step : 431 time: --> 0.24222862400114537 s, odometry: - [-10.06730213  29.95111576   3.14391868].\n",
      "Step : 432 time: --> 0.24436445501446724 s, odometry: - [-10.2914681   29.95059434   3.145135  ].\n",
      "Step : 433 time: --> 0.24469310501217842 s, odometry: - [-10.51636455  29.94979767   3.14840462].\n",
      "Step : 434 time: --> 0.24319093400239944 s, odometry: - [-10.73873135  29.94828289   3.15111155].\n",
      "Step : 435 time: --> 0.24298429998755455 s, odometry: - [-10.96181219  29.94615935   3.15255556].\n",
      "Step : 436 time: --> 0.2432896149903536 s, odometry: - [-11.18552084  29.94370675   3.15433402].\n",
      "Step : 437 time: --> 0.24347244100272655 s, odometry: - [-11.4113568   29.94082914   3.15650288].\n",
      "Step : 438 time: --> 0.24581006298959254 s, odometry: - [-11.63586084  29.93748148   3.1590982 ].\n",
      "Step : 439 time: --> 0.24458616499602795 s, odometry: - [-11.85871149  29.93357996   3.16164518].\n",
      "Step : 440 time: --> 0.2450180670171976 s, odometry: - [-12.07967428  29.92914851   3.16435875].\n",
      "Step : 441 time: --> 0.24359016498923303 s, odometry: - [-12.30137548  29.92410036   3.16731261].\n",
      "Step : 442 time: --> 0.24542650100588798 s, odometry: - [-12.52443368  29.91836205   3.16952965].\n",
      "Step : 443 time: --> 0.24703624200820923 s, odometry: - [-12.74723261  29.9121361    3.17159959].\n",
      "Step : 444 time: --> 0.24590714299678804 s, odometry: - [-12.96899514  29.90547968   3.17510799].\n",
      "Step : 445 time: --> 0.24569487901031972 s, odometry: - [-13.18957188  29.89808421   3.17847319].\n",
      "Step : 446 time: --> 0.24546015200018884 s, odometry: - [-13.40917701  29.88998138   3.18264478].\n",
      "Step : 447 time: --> 0.24733399699628353 s, odometry: - [-13.62909193  29.88094833   3.18681463].\n",
      "Step : 448 time: --> 0.24735627000033855 s, odometry: - [-13.84995429  29.87095368   3.19030308].\n",
      "Step : 449 time: --> 0.24504673999547957 s, odometry: - [-14.07271263  29.86009444   3.19403705].\n",
      "Step : 450 time: --> 0.24746859799325466 s, odometry: - [-14.29462904  29.84844549   3.19902718].\n",
      "Step : 451 time: --> 0.2440904319882393 s, odometry: - [-14.51539824  29.83575175   3.20395653].\n",
      "Step : 452 time: --> 0.24388032199442386 s, odometry: - [-14.73425855  29.82208505   3.20963504].\n",
      "Step : 453 time: --> 0.2443710679858923 s, odometry: - [-14.9521892   29.8072336    3.21565996].\n",
      "Step : 454 time: --> 0.24456829300522803 s, odometry: - [-15.17072542  29.79101755   3.22234212].\n",
      "Step : 455 time: --> 0.2433888020068407 s, odometry: - [-15.38972114  29.77329523   3.22967767].\n",
      "Step : 456 time: --> 0.24393292900919913 s, odometry: - [-15.60935655  29.75389845   3.23677715].\n",
      "Step : 457 time: --> 0.2447047529965639 s, odometry: - [-15.82975485  29.73285636   3.24487403].\n",
      "Step : 458 time: --> 0.24397949999570848 s, odometry: - [-16.04916159  29.71011481   3.25380607].\n",
      "Step : 459 time: --> 0.2443943159878254 s, odometry: - [-16.26821645  29.68543022   3.26255079].\n",
      "Step : 460 time: --> 0.24429262399673463 s, odometry: - [-16.48661258  29.65888384   3.27291553].\n",
      "Step : 461 time: --> 0.24455145898461342 s, odometry: - [-16.70381544  29.63019503   3.28415948].\n",
      "Step : 462 time: --> 0.24408981899917126 s, odometry: - [-16.92139616  29.59896335   3.29526807].\n",
      "Step : 463 time: --> 0.2439404269903898 s, odometry: - [-17.13908382  29.56524425   3.30593543].\n",
      "Step : 464 time: --> 0.2437724049985409 s, odometry: - [-17.35806764  29.52892831   3.31718608].\n",
      "Step : 465 time: --> 0.24448949100077152 s, odometry: - [-17.57665881  29.49014572   3.3291279 ].\n",
      "Step : 466 time: --> 0.2434348379969597 s, odometry: - [-17.79474578  29.44876041   3.34073458].\n",
      "Step : 467 time: --> 0.24557971601188183 s, odometry: - [-18.01164254  29.40498699   3.35187123].\n",
      "Step : 468 time: --> 0.24471109798550605 s, odometry: - [-18.22614455  29.35920503   3.36420389].\n",
      "Step : 469 time: --> 0.2438230680078268 s, odometry: - [-18.44080534  29.31061381   3.37758117].\n",
      "Step : 470 time: --> 0.24303155601024629 s, odometry: - [-18.65501258  29.25910358   3.39154744].\n",
      "Step : 471 time: --> 0.243285732999444 s, odometry: - [-18.86983935  29.20425964   3.40325757].\n",
      "Step : 472 time: --> 0.24445068499445916 s, odometry: - [-19.08383965  29.14694928   3.41592625].\n",
      "Step : 473 time: --> 0.24344369401037694 s, odometry: - [-19.29674724  29.08703084   3.42863221].\n",
      "Step : 474 time: --> 0.2432683620005846 s, odometry: - [-19.5083445   29.02456912   3.44227573].\n",
      "Step : 475 time: --> 0.24499070000648498 s, odometry: - [-19.71778384  28.95962516   3.4569195 ].\n",
      "Step : 476 time: --> 0.24390729101002218 s, odometry: - [-19.92523871  28.89195109   3.47137065].\n",
      "Step : 477 time: --> 0.2451261649876833 s, odometry: - [-20.13327513  28.82074504   3.4870515 ].\n",
      "Step : 478 time: --> 0.24272547900676728 s, odometry: - [-20.34095445  28.74600318   3.50266522].\n",
      "Step : 479 time: --> 0.24367114600539208 s, odometry: - [-20.54842423  28.66765681   3.51863443].\n",
      "Step : 480 time: --> 0.24483535300195217 s, odometry: - [-20.75598218  28.58546664   3.53236462].\n",
      "Step : 481 time: --> 0.24346264900267126 s, odometry: - [-20.9596633   28.50155865   3.54674607].\n",
      "Step : 482 time: --> 0.24322795300185682 s, odometry: - [-21.16135735  28.41505587   3.56208927].\n",
      "Step : 483 time: --> 0.2452591350078583 s, odometry: - [-21.36075582  28.32589119   3.57673167].\n",
      "Step : 484 time: --> 0.24371123799681663 s, odometry: - [-21.55895823  28.23375568   3.59242695].\n",
      "Step : 485 time: --> 0.24531840899586677 s, odometry: - [-21.75592677  28.13840626   3.60802735].\n",
      "Step : 486 time: --> 0.24368988700211047 s, odometry: - [-21.95318917  28.03908687   3.6233166 ].\n",
      "Step : 487 time: --> 0.24294222798943518 s, odometry: - [-22.14917072  27.93662693   3.63794428].\n",
      "Step : 488 time: --> 0.24557049398124217 s, odometry: - [-22.34382678  27.83120614   3.65269973].\n",
      "Step : 489 time: --> 0.24391571098566056 s, odometry: - [-22.53565067  27.72362879   3.66754899].\n",
      "Step : 490 time: --> 0.24434938599169254 s, odometry: - [-22.72624786  27.61298751   3.68194946].\n",
      "Step : 491 time: --> 0.2447200160175562 s, odometry: - [-22.91508422  27.49970179   3.69684432].\n",
      "Step : 492 time: --> 0.24395905999839307 s, odometry: - [-23.10224556  27.38359544   3.71183545].\n",
      "Step : 493 time: --> 0.2433773970156908 s, odometry: - [-23.28832526  27.26426045   3.7270628 ].\n",
      "Step : 494 time: --> 0.24338049301505088 s, odometry: - [-23.47241391  27.14220694   3.74168309].\n",
      "Step : 495 time: --> 0.24100768201053144 s, odometry: - [-23.65598443  27.01659522   3.75641006].\n",
      "Step : 496 time: --> 0.2421611839979887 s, odometry: - [-23.83623943  26.88931468   3.77159744].\n",
      "Step : 497 time: --> 0.24234266601502896 s, odometry: - [-24.01338555  26.76015354   3.78578923].\n",
      "Step : 498 time: --> 0.24314494900405406 s, odometry: - [-24.19092496  26.62680595   3.79968183].\n",
      "Step : 499 time: --> 0.24317548801004887 s, odometry: - [-24.36568614  26.49170723   3.81497775].\n",
      "Step : 500 time: --> 0.24447531600296496 s, odometry: - [-24.53846058  26.35387145   3.82998933].\n",
      "Step : 501 time: --> 0.24465886199474335 s, odometry: - [-24.70936065  26.2132815    3.8437065 ].\n",
      "Step : 502 time: --> 0.24382112000882625 s, odometry: - [-24.87736085  26.07116873   3.85879562].\n",
      "Step : 503 time: --> 0.2449612299948931 s, odometry: - [-25.04335866  25.92639683   3.87354332].\n",
      "Step : 504 time: --> 0.24473799400031568 s, odometry: - [-25.20866508  25.77787949   3.88943115].\n",
      "Step : 505 time: --> 0.24339984399080278 s, odometry: - [-25.37223445  25.62615792   3.90463736].\n",
      "Step : 506 time: --> 0.24503016798198224 s, odometry: - [-25.53319012  25.47224189   3.91870898].\n",
      "Step : 507 time: --> 0.24516399002075195 s, odometry: - [-25.69264923  25.31540238   3.93409769].\n",
      "Step : 508 time: --> 0.24499877800047398 s, odometry: - [-25.84930819  25.15650073   3.95007611].\n",
      "Step : 509 time: --> 0.2449537550210953 s, odometry: - [-26.0038381   24.99466615   3.96515312].\n",
      "Step : 510 time: --> 0.24315345899760724 s, odometry: - [-26.15568204  24.83076687   3.97955403].\n",
      "Step : 511 time: --> 0.24378340598940848 s, odometry: - [-26.30480483  24.6650815    3.99669294].\n",
      "Step : 512 time: --> 0.2429927579909563 s, odometry: - [-26.45180895  24.49601052   4.01318081].\n",
      "Step : 513 time: --> 0.24367109200358392 s, odometry: - [-26.59595932  24.32459389   4.02881672].\n",
      "Step : 514 time: --> 0.24377201798558235 s, odometry: - [-26.73626452  24.15235294   4.04377805].\n",
      "Step : 515 time: --> 0.24448668999969958 s, odometry: - [-26.87397598  23.97803369   4.05872137].\n",
      "Step : 516 time: --> 0.244068308994174 s, odometry: - [-27.00962458  23.80094853   4.07381753].\n",
      "Step : 517 time: --> 0.24484616400301457 s, odometry: - [-27.1424512   23.62201547   4.08969869].\n",
      "Step : 518 time: --> 0.2442377299964428 s, odometry: - [-27.2725058   23.44087544   4.10561338].\n",
      "Step : 519 time: --> 0.24359701201319695 s, odometry: - [-27.39977772  23.2575209    4.12113126].\n",
      "Step : 520 time: --> 0.24385672301054 s, odometry: - [-27.52390954  23.07263001   4.13701495].\n",
      "Step : 521 time: --> 0.24396093599498272 s, odometry: - [-27.64446232  22.88675719   4.15142506].\n",
      "Step : 522 time: --> 0.24328901700675487 s, odometry: - [-27.7617626   22.70006047   4.16561475].\n",
      "Step : 523 time: --> 0.24355393297970296 s, odometry: - [-27.87638548  22.51174524   4.18039244].\n",
      "Step : 524 time: --> 0.2441046320050955 s, odometry: - [-27.98819208  22.32179249   4.19574307].\n",
      "Step : 525 time: --> 0.24430400800704957 s, odometry: - [-28.09699509  22.13027724   4.21110643].\n",
      "Step : 526 time: --> 0.24341324400901795 s, odometry: - [-28.20328363  21.93630907   4.22639449].\n",
      "Step : 527 time: --> 0.24348988300561905 s, odometry: - [-28.30603164  21.74180413   4.24196596].\n",
      "Step : 528 time: --> 0.24919936698675155 s, odometry: - [-28.40525351  21.54667685   4.25756745].\n",
      "Step : 529 time: --> 0.24316874301433564 s, odometry: - [-28.50135596  21.35015458   4.27212519].\n",
      "Step : 530 time: --> 0.24273761300742627 s, odometry: - [-28.59554898  21.15021306   4.28765056].\n",
      "Step : 531 time: --> 0.2440381949990988 s, odometry: - [-28.68692231  20.94817946   4.30303413].\n",
      "Step : 532 time: --> 0.24243226800858975 s, odometry: - [-28.77542805  20.74418545   4.31843472].\n",
      "Step : 533 time: --> 0.24285387401282788 s, odometry: - [-28.8609206   20.53851872   4.33342891].\n",
      "Step : 534 time: --> 0.24514210899174213 s, odometry: - [-28.94301463  20.33235973   4.34932589].\n",
      "Step : 535 time: --> 0.24440082600712776 s, odometry: - [-29.02188501  20.12475364   4.36556634].\n",
      "Step : 536 time: --> 0.2448701100051403 s, odometry: - [-29.09716928  19.91645916   4.3812204 ].\n",
      "Step : 537 time: --> 0.2449108249992132 s, odometry: - [-29.16970001  19.70551044   4.39723917].\n",
      "Step : 538 time: --> 0.244270437002182 s, odometry: - [-29.23856381  19.4942816    4.41236078].\n",
      "Step : 539 time: --> 0.24413719798624517 s, odometry: - [-29.30389823  19.28309428   4.42694657].\n",
      "Step : 540 time: --> 0.24362754499912262 s, odometry: - [-29.36628367  19.0705056    4.44092657].\n",
      "Step : 541 time: --> 0.24373227599263192 s, odometry: - [-29.4252283   18.85872837   4.45570747].\n",
      "Step : 542 time: --> 0.24512497498095034 s, odometry: - [-29.48072482  18.64728998   4.47062034].\n",
      "Step : 543 time: --> 0.24413402700424194 s, odometry: - [-29.5331069   18.43486593   4.48509735].\n",
      "Step : 544 time: --> 0.24350296899676324 s, odometry: - [-29.58278675  18.22006976   4.50019905].\n",
      "Step : 545 time: --> 0.24420034401118756 s, odometry: - [-29.62942872  18.00356633   4.5152271 ].\n",
      "Step : 546 time: --> 0.2442755369991064 s, odometry: - [-29.6728501   17.78619531   4.53214215].\n",
      "Step : 547 time: --> 0.24573606999218464 s, odometry: - [-29.71233294  17.56952396   4.54738734].\n",
      "Step : 548 time: --> 0.2452851120084524 s, odometry: - [-29.74849469  17.35235655   4.56276825].\n",
      "Step : 549 time: --> 0.24403349600732327 s, odometry: - [-29.78123806  17.13514952   4.57610536].\n",
      "Step : 550 time: --> 0.2440609640032053 s, odometry: - [-29.81098061  16.91826222   4.59074904].\n",
      "Step : 551 time: --> 0.24472536700963973 s, odometry: - [-29.83754371  16.70096553   4.60471454].\n",
      "Step : 552 time: --> 0.24514160799980164 s, odometry: - [-29.86113418  16.48272214   4.61870853].\n",
      "Step : 553 time: --> 0.24498050498962404 s, odometry: - [-29.88166712  16.26418307   4.6342691 ].\n",
      "Step : 554 time: --> 0.2460911609977484 s, odometry: - [-29.89878736  16.04547562   4.64963751].\n",
      "Step : 555 time: --> 0.24481930600106716 s, odometry: - [-29.91252148  15.82689774   4.6656929 ].\n",
      "Step : 556 time: --> 0.24392295999825 s, odometry: - [-29.92274144  15.60819557   4.67975862].\n",
      "Step : 557 time: --> 0.24470450299978255 s, odometry: - [-29.92992145  15.38823282   4.69516665].\n",
      "Step : 558 time: --> 0.24458146700263023 s, odometry: - [-29.93372598  15.16734791   4.71008596].\n",
      "Step : 559 time: --> 0.2441169230043888 s, odometry: - [-29.93423554  14.94609204   4.72583667].\n",
      "Step : 560 time: --> 0.2439520120024681 s, odometry: - [-29.93127779  14.72616024   4.7405582 ].\n",
      "Step : 561 time: --> 0.24412138499319552 s, odometry: - [-29.92504193  14.50484735   4.75547692].\n",
      "Step : 562 time: --> 0.24570763398706913 s, odometry: - [-29.91553911  14.28443926   4.77120802].\n",
      "Step : 563 time: --> 0.24429720900952817 s, odometry: - [-29.90257641  14.06431075   4.78670649].\n",
      "Step : 564 time: --> 0.24543073499202728 s, odometry: - [-29.88617179  13.84398029   4.80152606].\n",
      "Step : 565 time: --> 0.24551310999691486 s, odometry: - [-29.86655432  13.62448147   4.81714434].\n",
      "Step : 566 time: --> 0.2456628419905901 s, odometry: - [-29.84343627  13.40460322   4.83272653].\n",
      "Step : 567 time: --> 0.24556312799453736 s, odometry: - [-29.81704117  13.18632083   4.84867263].\n",
      "Step : 568 time: --> 0.2449476999938488 s, odometry: - [-29.78728681  12.96934745   4.86357097].\n",
      "Step : 569 time: --> 0.24522673898935318 s, odometry: - [-29.75425121  12.75249933   4.87917471].\n",
      "Step : 570 time: --> 0.2452260669916868 s, odometry: - [-29.71794267  12.53682597   4.89459128].\n",
      "Step : 571 time: --> 0.245248340010643 s, odometry: - [-29.67850051  12.32275223   4.90967857].\n",
      "Step : 572 time: --> 0.24561071601510048 s, odometry: - [-29.63590959  12.10968022   4.92272013].\n",
      "Step : 573 time: --> 0.24461937199532985 s, odometry: - [-29.59064674  11.89766496   4.9363364 ].\n",
      "Step : 574 time: --> 0.24493452501296997 s, odometry: - [-29.54242929  11.68596944   4.94949568].\n",
      "Step : 575 time: --> 0.24507523800432682 s, odometry: - [-29.49111497  11.47362167   4.96281618].\n",
      "Step : 576 time: --> 0.24669844801723956 s, odometry: - [-29.43719997  11.26284911   4.9765674 ].\n",
      "Step : 577 time: --> 0.24502299499511718 s, odometry: - [-29.37964597  11.05008068   4.99027284].\n",
      "Step : 578 time: --> 0.24594399400055408 s, odometry: - [-29.31914129  10.83798046   5.00346922].\n",
      "Step : 579 time: --> 0.24560574601590635 s, odometry: - [-29.25624761  10.62804767   5.0167982 ].\n",
      "Step : 580 time: --> 0.24600732700526715 s, odometry: - [-29.1907904   10.41970069   5.0318629 ].\n",
      "Step : 581 time: --> 0.24380805599689484 s, odometry: - [-29.1221312   10.2121492    5.04822643].\n",
      "Step : 582 time: --> 0.24429120299220086 s, odometry: - [-29.04964089  10.00447647   5.06404848].\n",
      "Step : 583 time: --> 0.24421481500566006 s, odometry: - [-28.97430171   9.7991424    5.078753  ].\n",
      "Step : 584 time: --> 0.2438962140083313 s, odometry: - [-28.89571095   9.5943115    5.09401417].\n",
      "Step : 585 time: --> 0.2441925910115242 s, odometry: - [-28.81382115   9.3902494    5.10802503].\n",
      "Step : 586 time: --> 0.24183518798649312 s, odometry: - [-28.72834642   9.18559726   5.12205005].\n",
      "Step : 587 time: --> 0.2423270050138235 s, odometry: - [-28.64068656   8.98372223   5.13546693].\n",
      "Step : 588 time: --> 0.2428663659989834 s, odometry: - [-28.55073072   8.78393997   5.14975578].\n",
      "Step : 589 time: --> 0.24363620199263095 s, odometry: - [-28.45777394   8.58513073   5.16555452].\n",
      "Step : 590 time: --> 0.2438703460097313 s, odometry: - [-28.36158447   8.38760231   5.1800048 ].\n",
      "Step : 591 time: --> 0.2439557400047779 s, odometry: - [-28.26262205   8.19162554   5.19442966].\n",
      "Step : 592 time: --> 0.24404232899844647 s, odometry: - [-28.16155331   7.99845407   5.20875627].\n",
      "Step : 593 time: --> 0.24369841900467873 s, odometry: - [-28.05777732   7.80684225   5.2245915 ].\n",
      "Step : 594 time: --> 0.24359003798663617 s, odometry: - [-27.95099167   7.61691802   5.23905491].\n",
      "Step : 595 time: --> 0.24308776699006557 s, odometry: - [-27.84152378   7.42864999   5.2543793 ].\n",
      "Step : 596 time: --> 0.2431420920044184 s, odometry: - [-27.7292128    7.24212976   5.26974907].\n",
      "Step : 597 time: --> 0.24353638999164104 s, odometry: - [-27.61349228   7.05646539   5.28511611].\n",
      "Step : 598 time: --> 0.24406856498122215 s, odometry: - [-27.49507306   6.87281927   5.30046935].\n",
      "Step : 599 time: --> 0.24421466600894928 s, odometry: - [-27.37285527   6.68952348   5.31427816].\n",
      "Step : 600 time: --> 0.24384811100363732 s, odometry: - [-27.24722542   6.5066332    5.32794578].\n",
      "Step : 601 time: --> 0.24380401499569415 s, odometry: - [-27.11960889   6.32618569   5.34180175].\n",
      "Step : 602 time: --> 0.24445852199196816 s, odometry: - [-26.98954187   6.14757512   5.35643681].\n",
      "Step : 603 time: --> 0.24377310098707675 s, odometry: - [-26.85714701   5.97124955   5.36957954].\n",
      "Step : 604 time: --> 0.24437656500935553 s, odometry: - [-26.72240559   5.79662651   5.38358498].\n",
      "Step : 605 time: --> 0.24435942098498345 s, odometry: - [-26.58422354   5.62263812   5.3994913 ].\n",
      "Step : 606 time: --> 0.24385153698921203 s, odometry: - [-26.44351013   5.45113599   5.41471907].\n",
      "Step : 607 time: --> 0.24362773299217225 s, odometry: - [-26.30045087   5.28209104   5.42932847].\n",
      "Step : 608 time: --> 0.243279555991292 s, odometry: - [-26.15581347   5.1161592    5.44335536].\n",
      "Step : 609 time: --> 0.2429697929918766 s, odometry: - [-26.00878274   4.95218308   5.45804455].\n",
      "Step : 610 time: --> 0.24238683399558067 s, odometry: - [-25.85900453   4.7900002    5.47195286].\n",
      "Step : 611 time: --> 0.24277184300124646 s, odometry: - [-25.70640669   4.6293069    5.48640146].\n",
      "Step : 612 time: --> 0.24293928898870945 s, odometry: - [-25.5512612    4.47058769   5.50140974].\n",
      "Step : 613 time: --> 0.24357615800201893 s, odometry: - [-25.39495536   4.31541024   5.5167496 ].\n",
      "Step : 614 time: --> 0.24343076199293137 s, odometry: - [-25.23667718   4.16302373   5.53229814].\n",
      "Step : 615 time: --> 0.24219285199046134 s, odometry: - [-25.07631653   4.01336636   5.54625768].\n",
      "Step : 616 time: --> 0.24271284300088883 s, odometry: - [-24.91402607   3.86609241   5.56058427].\n",
      "Step : 617 time: --> 0.24285666400194167 s, odometry: - [-24.74962858   3.72114638   5.57579849].\n",
      "Step : 618 time: --> 0.24295730701088905 s, odometry: - [-24.58262892   3.57836249   5.59083487].\n",
      "Step : 619 time: --> 0.24315080098807812 s, odometry: - [-24.41387182   3.43841303   5.6069167 ].\n",
      "Step : 620 time: --> 0.2435012039989233 s, odometry: - [-24.24362353   3.30178733   5.62269179].\n",
      "Step : 621 time: --> 0.24189936600625514 s, odometry: - [-24.07277937   3.16905919   5.63624306].\n",
      "Step : 622 time: --> 0.24233703899383546 s, odometry: - [-23.89981384   3.03840264   5.64995979].\n",
      "Step : 623 time: --> 0.24466093499958516 s, odometry: - [-23.72464052   2.90981375   5.66533003].\n",
      "Step : 624 time: --> 0.2580765550136566 s, odometry: - [-23.54590981   2.7827941    5.68046115].\n",
      "Step : 625 time: --> 0.2473308689892292 s, odometry: - [-23.36597827   2.65897539   5.69542909].\n",
      "Step : 626 time: --> 0.24649663600325583 s, odometry: - [-23.1843932    2.53798328   5.7117529 ].\n",
      "Step : 627 time: --> 0.24504433600604533 s, odometry: - [-23.00044794   2.41970808   5.7275674 ].\n",
      "Step : 628 time: --> 0.24490581700205802 s, odometry: - [-22.8157837    2.30505713   5.74363898].\n",
      "Step : 629 time: --> 0.24552186499536038 s, odometry: - [-22.62970205   2.193629     5.75843679].\n",
      "Step : 630 time: --> 0.24433531598746777 s, odometry: - [-22.43988138   2.0837448    5.77191003].\n",
      "Step : 631 time: --> 0.24529481099545955 s, odometry: - [-22.24941383   1.97688599   5.7855163 ].\n",
      "Step : 632 time: --> 0.24572170899808407 s, odometry: - [-22.05749977   1.87262298   5.80007429].\n",
      "Step : 633 time: --> 0.24370837301015855 s, odometry: - [-21.86418254   1.77121428   5.81443258].\n",
      "Step : 634 time: --> 0.24273622201383113 s, odometry: - [-21.66918206   1.67246646   5.82804072].\n",
      "Step : 635 time: --> 0.2416529519855976 s, odometry: - [-21.47020596   1.57508438   5.84145261].\n",
      "Step : 636 time: --> 0.24060055300593375 s, odometry: - [-21.26979241   1.48030902   5.85473656].\n",
      "Step : 637 time: --> 0.2403992410004139 s, odometry: - [-21.07001129   1.38906003   5.86744041].\n",
      "Step : 638 time: --> 0.23936979798972607 s, odometry: - [-20.86863385   1.30015622   5.87985666].\n",
      "Step : 639 time: --> 0.2384328559935093 s, odometry: - [-20.6670985    1.21415656   5.89359738].\n",
      "Step : 640 time: --> 0.23729075899720192 s, odometry: - [-20.46332642   1.13049319   5.90608535].\n",
      "Step : 641 time: --> 0.23780038100481032 s, odometry: - [-20.25775891   1.04907738   5.91700007].\n",
      "Step : 642 time: --> 0.235347810998559 s, odometry: - [-20.05157378   0.9700093    5.92812325].\n",
      "Step : 643 time: --> 0.2346924799978733 s, odometry: - [-19.84502793   0.89342711   5.93767784].\n",
      "Step : 644 time: --> 0.23389505998790264 s, odometry: - [-19.63834208   0.81903144   5.95116277].\n",
      "Step : 645 time: --> 0.23275906099379062 s, odometry: - [-19.43096882   0.74753199   5.96354307].\n",
      "Step : 646 time: --> 0.23183925199508668 s, odometry: - [-19.22188167   0.67832573   5.97733612].\n",
      "Step : 647 time: --> 0.2299687210023403 s, odometry: - [-19.01336405   0.61248487   5.99142626].\n",
      "Step : 648 time: --> 0.23013784800469875 s, odometry: - [-18.80236712   0.54911627   6.00539665].\n",
      "Step : 649 time: --> 0.2293006500005722 s, odometry: - [-18.59046131   0.48868886   6.01935008].\n",
      "Step : 650 time: --> 0.2285784550011158 s, odometry: - [-18.37688476   0.43099491   6.03401863].\n",
      "Step : 651 time: --> 0.22775879099965096 s, odometry: - [-18.16463326   0.37698658   6.05072848].\n",
      "Step : 652 time: --> 0.2250238709896803 s, odometry: - [-17.95157283   0.32654742   6.06640316].\n",
      "Step : 653 time: --> 0.22397813400626182 s, odometry: - [-17.73670167   0.27922354   6.08176116].\n",
      "Step : 654 time: --> 0.22362930500507355 s, odometry: - [-17.52129624   0.23523923   6.0975985 ].\n",
      "Step : 655 time: --> 0.22211017099022864 s, odometry: - [-17.3019331    0.1940544    6.11463118].\n",
      "Step : 656 time: --> 0.22166687400639057 s, odometry: - [-17.08193116   0.15661695   6.13179093].\n",
      "Step : 657 time: --> 0.22079279498755933 s, odometry: - [-16.85994227   0.12274994   6.1483874 ].\n",
      "Step : 658 time: --> 0.22016943301260472 s, odometry: - [-16.63799768   0.09264974   6.16416204].\n",
      "Step : 659 time: --> 0.21961776898801327 s, odometry: - [-16.41524628   0.06601123   6.17872652].\n",
      "Step : 660 time: --> 0.21804669399559498 s, odometry: - [-16.19245457   0.04265366   6.19095962].\n",
      "Step : 661 time: --> 0.21768652398884297 s, odometry: - [-15.96926017   0.02201084   6.20458208].\n",
      "Step : 662 time: --> 0.21687496200203896 s, odometry: - [-1.57458032e+01  4.41014038e-03  6.21796072e+00].\n",
      "Step : 663 time: --> 0.21511933799088 s, odometry: - [-1.55226202e+01 -1.01675519e-02  6.22913137e+00].\n",
      "Step : 664 time: --> 0.21443618899583816 s, odometry: - [-15.29838674  -0.02230007   6.23990155].\n",
      "Step : 665 time: --> 0.21367138999700547 s, odometry: - [-15.07178471  -0.03211439   6.24971177].\n",
      "Step : 666 time: --> 0.21166004799306393 s, odometry: - [-14.84562473  -0.03968759   6.25817197].\n",
      "Step : 667 time: --> 0.21049197500944136 s, odometry: - [-14.62177823  -0.04528791   6.26573852].\n",
      "Step : 668 time: --> 0.20839197100698947 s, odometry: - [-14.396952    -0.0492108    6.27041487].\n",
      "Step : 669 time: --> 0.20698006500303745 s, odometry: - [-14.17294178  -0.05207167   6.27563746].\n",
      "Step : 670 time: --> 0.20608014000952243 s, odometry: - [-13.94966496  -0.05375696   6.28125594].\n",
      "Step : 671 time: --> 0.20455019702017307 s, odometry: - [-13.72274686  -0.05419477   6.28570712].\n",
      "Step : 672 time: --> 0.20250155299901962 s, odometry: - [-13.49720359  -0.05362599   6.28789984].\n",
      "Step : 673 time: --> 0.20164684000611305 s, odometry: - [-13.27383338  -0.0525729    6.29253673].\n",
      "Step : 674 time: --> 0.20015967801213264 s, odometry: - [-13.05232391  -0.05050141   6.29496205].\n",
      "Step : 675 time: --> 0.19795185999572276 s, odometry: - [-12.83154993  -0.04790129   6.29801731].\n",
      "Step : 676 time: --> 0.19710583800077439 s, odometry: - [-12.60935639  -0.04460547   6.30022819].\n",
      "Step : 677 time: --> 0.19543338598310947 s, odometry: - [-12.38772093  -0.0408278    6.30151306].\n",
      "Step : 678 time: --> 0.19421971398591995 s, odometry: - [-12.16512673  -0.03674769   6.3045702 ].\n",
      "Step : 679 time: --> 0.19300558398663997 s, odometry: - [-11.9431776   -0.03200061   6.30434389].\n",
      "Step : 680 time: --> 0.1909757439941168 s, odometry: - [-11.72051723  -0.02728873   6.30440597].\n",
      "Step : 681 time: --> 0.1884198240041733 s, odometry: - [-11.49959688  -0.02259995   6.30481241].\n",
      "Step : 682 time: --> 0.18912613801658154 s, odometry: - [-11.27988445  -0.01784746   6.30760632].\n",
      "Step : 683 time: --> 0.18694080799818039 s, odometry: - [-11.06109399  -0.01250331   6.30885199].\n",
      "Step : 684 time: --> 0.18505025099217892 s, odometry: - [-1.08422387e+01 -6.88479165e-03  6.31059817e+00].\n",
      "Step : 685 time: --> 0.18261371299624443 s, odometry: - [-1.06211690e+01 -8.23118146e-04  6.31173729e+00].\n",
      "Step : 686 time: --> 0.1820696759968996 s, odometry: - [-1.04012971e+01  5.45636484e-03  6.31163101e+00].\n",
      "Step : 687 time: --> 0.17906004199385642 s, odometry: - [-10.18156647   0.01170844   6.3117744 ].\n",
      "Step : 688 time: --> 0.17822577901184558 s, odometry: - [-9.96174325  0.0179947   6.31065026].\n",
      "Step : 689 time: --> 0.17792922301590441 s, odometry: - [-9.74054719  0.02407137  6.31112978].\n",
      "Step : 690 time: --> 0.1759159269928932 s, odometry: - [-9.51868625  0.03027277  6.3123703 ].\n",
      "Step : 691 time: --> 0.1740116920173168 s, odometry: - [-9.29612437  0.03677008  6.31346274].\n",
      "Step : 692 time: --> 0.1739101969897747 s, odometry: - [-9.07419353  0.04349163  6.31317441].\n",
      "Step : 693 time: --> 0.17189721299707889 s, odometry: - [-8.85299621  0.05012713  6.31323856].\n",
      "Step : 694 time: --> 0.1832720120102167 s, odometry: - [-8.62886391  0.05686507  6.31263106].\n",
      "Step : 695 time: --> 0.1691595789939165 s, odometry: - [-8.40542505  0.06344629  6.3122419 ].\n",
      "Step : 696 time: --> 0.16705084800720216 s, odometry: - [-8.18344443  0.06989811  6.31204983].\n",
      "Step : 697 time: --> 0.16509419898688793 s, odometry: - [-7.96364415  0.0762443   6.31185935].\n",
      "Step : 698 time: --> 0.16225876998901367 s, odometry: - [-7.74310256  0.08256986  6.3115768 ].\n",
      "Step : 699 time: --> 0.1606356939971447 s, odometry: - [-7.52412835  0.08878853  6.31214007].\n",
      "Step : 700 time: --> 0.15824443399906157 s, odometry: - [-7.30626479  0.09509848  6.31071512].\n",
      "Step : 701 time: --> 0.15818106098473073 s, odometry: - [-7.08841708  0.1010973   6.30927587].\n",
      "Step : 702 time: --> 0.15646432200074195 s, odometry: - [-6.87058652  0.10678192  6.30876329].\n",
      "Step : 703 time: --> 0.15449153500795365 s, odometry: - [-6.65246645  0.1123622   6.30862612].\n",
      "Step : 704 time: --> 0.15315402701497077 s, odometry: - [-6.43982596  0.11777312  6.31018417].\n",
      "Step : 705 time: --> 0.15001042300462722 s, odometry: - [-6.23178454  0.12339137  6.30997859].\n",
      "Step : 706 time: --> 0.14993888500332833 s, odometry: - [-6.02645604  0.12889411  6.30994059].\n",
      "Step : 707 time: --> 0.14746790000796317 s, odometry: - [-5.82461536  0.1342957   6.31206172].\n",
      "Step : 708 time: --> 0.14635157999396325 s, odometry: - [-5.62522998  0.14005484  6.31295337].\n",
      "Step : 709 time: --> 0.1444175690114498 s, odometry: - [-5.43242896  0.14579584  6.3132607 ].\n",
      "Step : 710 time: --> 0.1432826580107212 s, odometry: - [-5.24245595  0.15151108  6.31196032].\n",
      "Step : 711 time: --> 0.14101286000013352 s, odometry: - [-5.05461629  0.15691766  6.31088913].\n",
      "Step : 712 time: --> 0.140673720985651 s, odometry: - [-4.86954556  0.16204614  6.30974219].\n",
      "Step : 713 time: --> 0.13937385401129723 s, odometry: - [-4.68427359  0.16696754  6.30873252].\n",
      "Step : 714 time: --> 0.13778671799600126 s, odometry: - [-4.50821337  0.17146637  6.30828144].\n",
      "Step : 715 time: --> 0.1360177769958973 s, odometry: - [-4.33561298  0.17579888  6.30477547].\n",
      "Step : 716 time: --> 0.13501117999851703 s, odometry: - [-4.16239654  0.17953923  6.30172334].\n",
      "Step : 717 time: --> 0.13381978200376035 s, odometry: - [-3.99217377  0.18269519  6.30107444].\n",
      "Step : 718 time: --> 0.13302965998649596 s, odometry: - [-3.82673371  0.18565509  6.30212068].\n",
      "Step : 719 time: --> 0.131240851983428 s, odometry: - [-3.66543968  0.18870961  6.30441438].\n",
      "Step : 720 time: --> 0.13044986301660538 s, odometry: - [-3.50659508  0.19208224  6.30737227].\n",
      "Step : 721 time: --> 0.12943250501155854 s, odometry: - [-3.34761187  0.19592831  6.3082918 ].\n",
      "Step : 722 time: --> 0.12812659698724746 s, odometry: - [-3.20209652  0.19958246  6.31127791].\n",
      "Step : 723 time: --> 0.12629360200464726 s, odometry: - [-3.06003704  0.20357433  6.31080296].\n",
      "Step : 724 time: --> 0.12648430299758912 s, odometry: - [-2.91942008  0.20745883  6.30763161].\n",
      "Step : 725 time: --> 0.12399681301414966 s, odometry: - [-2.7815073   0.21083096  6.31279474].\n",
      "Step : 726 time: --> 0.12477062399685383 s, odometry: - [-2.64580816  0.21485011  6.31702655].\n",
      "Step : 727 time: --> 0.12204766000807285 s, odometry: - [-2.51391749  0.21931516  6.31606248].\n",
      "Step : 728 time: --> 0.12216302400827408 s, odometry: - [-2.37974032  0.22372811  6.31363695].\n",
      "Step : 729 time: --> 0.12063972200453281 s, odometry: - [-2.24555433  0.22781556  6.31338761].\n",
      "Step : 730 time: --> 0.12095862199366093 s, odometry: - [-2.12669245  0.23140656  6.31455505].\n",
      "Step : 731 time: --> 0.11869705501198768 s, odometry: - [-2.01121673  0.23503019  6.31143895].\n",
      "Step : 732 time: --> 0.1178238880187273 s, odometry: - [-1.89937703  0.23819091  6.30960435].\n",
      "Step : 733 time: --> 0.11604108899831772 s, odometry: - [-1.79214544  0.24102452  6.30645494].\n",
      "Step : 734 time: --> 0.11620712700486183 s, odometry: - [-1.69282895  0.243336    6.30441957].\n",
      "Step : 735 time: --> 0.11523690098524093 s, odometry: - [-1.60045515  0.24529778  6.30077784].\n",
      "Step : 736 time: --> 0.11425930002331734 s, odometry: - [-1.51579435  0.24678734  6.29501715].\n",
      "Step : 737 time: --> 0.11345247098803521 s, odometry: - [-1.42738776  0.2478334   6.2918936 ].\n",
      "Step : 738 time: --> 0.11298944099247456 s, odometry: - [-1.345983    0.24854231  6.29144896].\n",
      "Step : 739 time: --> 0.1115052249878645 s, odometry: - [-1.26399614  0.24921984  6.29097445].\n",
      "Step : 740 time: --> 0.1117830459922552 s, odometry: - [-1.18217794  0.24985714  6.28730953].\n",
      "Step : 741 time: --> 0.11075191098451614 s, odometry: - [-1.11104837  0.2501505   6.29157242].\n",
      "Step : 742 time: --> 0.10933680699765683 s, odometry: - [-1.03773545  0.2507654   6.29340598].\n",
      "Step : 743 time: --> 0.10754937799274922 s, odometry: - [-0.9684069   0.25147401  6.30032599].\n",
      "Step : 744 time: --> 0.1087769750058651 s, odometry: - [-0.89713192  0.25269583  6.30556538].\n",
      "Step : 745 time: --> 0.10743318200111389 s, odometry: - [-0.83212225  0.25415099  6.30835972].\n",
      "Step : 746 time: --> 0.10706331300735474 s, odometry: - [-0.76548971  0.25582878  6.30662885].\n",
      "Step : 747 time: --> 0.10686047899723053 s, odometry: - [-0.70393846  0.25727203  6.30126222].\n",
      "Step : 748 time: --> 0.10619827100634575 s, odometry: - [-0.64106459  0.25840872  6.30487392].\n",
      "Step : 749 time: --> 0.10482525099813939 s, odometry: - [-0.57888298  0.25975756  6.31097807].\n",
      "Step : 750 time: --> 0.1052917690128088 s, odometry: - [-0.51966824  0.26140372  6.31534288].\n",
      "Step : 751 time: --> 0.10323167398571968 s, odometry: - [-0.45703826  0.26341845  6.31527875].\n",
      "Step : 752 time: --> 0.10432610601186752 s, odometry: - [-0.39552359  0.26539334  6.31339989].\n",
      "Step : 753 time: --> 0.10297326500713826 s, odometry: - [-0.33884503  0.26710638  6.31462937].\n",
      "Step : 754 time: --> 0.10266048699617386 s, odometry: - [-0.28089761  0.26892909  6.32639758].\n",
      "Step : 755 time: --> 0.10197003500163555 s, odometry: - [-0.2265341   0.27127972  6.33899391].\n",
      "Step : 756 time: --> 0.10122771100699901 s, odometry: - [-0.17926995  0.27392021  6.35347895].\n",
      "Step : 757 time: --> 0.1014257269948721 s, odometry: - [-0.12535557  0.2777163   6.36995331].\n",
      "Step : 758 time: --> 0.10070400400459767 s, odometry: - [-0.07835936  0.28180433  6.38706573].\n",
      "Step : 759 time: --> 0.10091712799668312 s, odometry: - [-0.02686829  0.28717257  6.40530743].\n",
      "End of sequence\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x900 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Imports\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scripts.diffdrive import DiffDriveVehicle\n",
    "from scripts.animation import Animator\n",
    "from scripts.mppi import MPPIControllerDiffDrive\n",
    "from scripts.utils import curr_time, debug_lock, plot_ref_vs_tracked_path, compute_erros, results_inputs\n",
    "\n",
    "# Setup simulation parameters\n",
    "# OBSTACLE_CIRCLES = np.array([+20.0,+20.0,1.0])\n",
    "# Obstacles are deifned in the global/inertial coordinate frame\n",
    "\n",
    "TRACK_TYPE = \"oval_path\" # \"oval\", \"figure_eight\"\n",
    "show_animation = False # Default true\n",
    "save_animation = False # Default False\n",
    "delta_t = 0.1 # [sec]\n",
    "sim_steps = 10000 # [steps]\n",
    "num_samples = 100 # [int]\n",
    "horizon_ = 20 # [int]\n",
    "print(f\"[INFO] delta_t : {delta_t:.2f}[s] , sim_steps : {sim_steps}[steps], total_sim_time : {delta_t*sim_steps:.2f}[s]\")\n",
    "actual_steps = 0\n",
    "\n",
    "# Load and visualize reference path\n",
    "if (TRACK_TYPE == \"oval_path\"):\n",
    "    ref_path = np.genfromtxt('./data/ovalpath_diff.csv', delimiter=',', skip_header=1)\n",
    "    \n",
    "    OBSTACLE_CIRCLES = np.array([\n",
    "    [+ 10.0, +5.0, 4.0], # pos_x, pos_y, radius [m] in the global frame\n",
    "    [+10.0, 33.0, 2.0], \n",
    "    ])\n",
    "\n",
    "elif (TRACK_TYPE == \"figure_eight\"):\n",
    "    ref_path = np.genfromtxt('./data/figure_eight.csv', delimiter=',', skip_header=1)\n",
    "\n",
    "    OBSTACLE_CIRCLES = np.array([\n",
    "    [+ 25.0, +30.0, 1.0], # pos_x, pos_y, radius [m] in the global frame\n",
    "    [+25.0, 32.0, 1.0], \n",
    "])\n",
    "\n",
    "else:\n",
    "    raise ValueError(f\"Requested path not available\")\n",
    "\n",
    "# Define vehicle type and MPPI\n",
    "init_state = np.array([0, 0, 0.0]) # [x,y,theta]\n",
    "vehicle = DiffDriveVehicle(delta_t=delta_t,\n",
    "                           ref_path=ref_path[:, 0:2], # np.ndarray([])\n",
    "                           abs_vb_val= 5.0, #[m/s]\n",
    "                           abs_omega_val=1.5, # [rad/s]\n",
    "                           obstacle_circles = OBSTACLE_CIRCLES,\n",
    "                           init_state=init_state)\n",
    "\n",
    "animator = Animator(vehicle_model=vehicle)\n",
    "if TRACK_TYPE == \"oval_path\":\n",
    "    aa = 80 # x,y weight\n",
    "    bb = 1 # yaw weight\n",
    "    cc = 80 # velocity weight\n",
    "else:\n",
    "    aa = 100.0 # x,y weight\n",
    "    bb = 20.0 # yaw weight\n",
    "    cc = 60.0 # velocity weight\n",
    "\n",
    "dd1 = 0.01\n",
    "dd2 = 0.01\n",
    "cost_arr = np.array([aa, aa, bb, cc])\n",
    "sigma_arr = np.array([[dd1, 0.0], [0.0, dd2]])\n",
    "\n",
    "# Define MPPI object\n",
    "# initialize a mppi controller for the vehicle\n",
    "mppi = MPPIControllerDiffDrive(\n",
    "    vehicle_model = vehicle,\n",
    "    delta_t = delta_t*2.0, # [s]\n",
    "    abs_vb_val = vehicle.abs_vb_val, # [m/s]\n",
    "    abs_omega_val = vehicle.abs_omega_val, # [rad/s]\n",
    "    ref_path = ref_path, # ndarray, size is <num_of_waypoints x 2>\n",
    "    horizon_step_T = horizon_, # [steps]\n",
    "    number_of_samples_K = num_samples, # [samples]\n",
    "    param_exploration = 0.05,\n",
    "    param_lambda = 50, # larger value of lambda heavily weighs low-cost path\n",
    "    param_alpha = 0.98,\n",
    "    sigma_matrix = sigma_arr,\n",
    "    stage_cost_weight = cost_arr, # weight for [x, y, yaw, v]\n",
    "    terminal_cost_weight = cost_arr, # weight for [x, y, yaw, v]\n",
    "    obstacle_circles = OBSTACLE_CIRCLES, # [obs_x, obs_y, obs_radius]\n",
    "    collision_safety_margin_rate = 1.2, # safety margin for collision check\n",
    ")\n",
    "\n",
    "# simulation loop\n",
    "warm_up_step = -1\n",
    "time_per_step = []\n",
    "done_flag = False\n",
    "tracked_path = [] # Odometry of robot\n",
    "# Main loop\n",
    "for i in range(sim_steps):\n",
    "    # get current state of vehicle\n",
    "    current_state = vehicle.get_state() # [x,y,yaw]\n",
    "    tt = curr_time()\n",
    "    # calculate input force with MPPI\n",
    "    optim_u, optim_u_seq, optimal_traj, sampled_traj_list, done_flag = mppi.calc_control_input(observed_x = current_state)\n",
    "    if (done_flag == False):\n",
    "        tt2 = curr_time()\n",
    "        tt_s = (tt2 - tt)/1000\n",
    "        time_per_step.append(tt_s)\n",
    "        # Give an initial velocity\n",
    "        if i<=warm_up_step:\n",
    "            optim_u = [1.0,0]\n",
    "        vehicle.update(u=optim_u, x_t_prev= current_state, delta_t=delta_t, \n",
    "                    optimal_traj=optimal_traj[:, 0:2], \n",
    "                    sampled_traj_list=sampled_traj_list[:, :, 0:2])\n",
    "        tracked_path.append(vehicle.state.copy())\n",
    "        if show_animation:\n",
    "            animator.draw_frame(vehicle.out_arr)\n",
    "        print(f\"Step : {i} time: --> {tt_s} s, odometry: - {vehicle.state.copy()}.\")\n",
    "        actual_steps+=1\n",
    "    else:\n",
    "        print(f\"End of sequence\")\n",
    "        break\n",
    "if show_animation:\n",
    "    animator.show_animation(interval_ms=delta_t*1000) # show animation\n",
    "if save_animation:\n",
    "    animator.save_animation(\"result.mp4\", interval=int(delta_t * 1000), movie_writer=\"ffmpeg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE for X-position: 0.8477062060029542 m\n",
      "RMSE for Y-position: 0.23995582893456105 m\n",
      "RMSE for Yaw : 1.6873056717107384 degree\n",
      "Mean linear velocity: 2.0217406300351564 m/s\n",
      "Mean angular velocity: 0.08428036090387671 rad/s\n",
      "Actual number of steps: 760 and total simulation time: 76.00 seconds\n",
      "Average time per step: 0.236 ms\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiQAAAK9CAYAAAAUmnf7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAADS90lEQVR4nOzdeXhM1xsH8O8kmWyIELIREvu+RWqnqCiqVapFa/drFdVKVdHF0hZVVTul1mpRa60ldmqpJWqnCIksQiyJrJPM+f1xzMy9syQzyUzu3Mn7eZ48uffOnXvfM+s755x7joIxxkAIIYQQIiEnqQMghBBCCKGEhBBCCCGSo4SEEEIIIZKjhIQQQgghkqOEhBBCCCGSo4SEEEIIIZKjhIQQQgghkqOEhBBCCCGSo4SEEEIIIZKjhIQQQgghkqOEhBBCCCGSo4SEEIlMnToVderUgVqtFm1//vw5PvnkEwQGBsLd3R2NGjXC+vXrRfssX74cFSpUQFpaWqFiWLVqFRQKBc6ePZvvPnfv3i3UuRyFrR8P/eOfOHECkydPxtOnT616niFDhkCpVCI7O9vkPl27doWnpydiYmKsem5CjKGEhBAJxMfHY+bMmZg6dSqcnMRvw549e2L16tWYNGkS9uzZg7CwMPTt2xe///67dp+BAweiRIkSmDlzps1j7datG06ePImAgACbn4sYPt4nTpzAlClTrJ6QNGjQADk5Obhx44bR2/fu3Ys9e/Zg/PjxqFSpklXPTYgxlJAQIoG5c+fC29sbPXv2FG3fvXs3IiMjsWjRInzwwQdo3749li1bhk6dOuGzzz5Dbm4uAMDFxQUffPAB5s6di/T0dJvGWr58eTRv3hxubm42PU9h2PoxKEpF9Xg3aNAAAHD58mWD23JychAREYHg4GCMGzfOpnEQokEJCSFWMmjQIAQHBxtsnzx5MhQKhXY9Ozsby5cvR79+/QxqR7Zu3YqSJUuid+/eou2DBw9GfHw8Tp8+rd327rvvIiUlxaA5x9r0mxA05bly5Qr69u2L0qVLw8/PD0OGDMGzZ88M7v/ff/+hX79+8PX1hZubG2rXro2FCxeK9rl16xYGDx6M6tWrw9PTExUqVED37t1x6dIlg+Npzn/+/Hm89dZbKFOmDKpWrWo09m3btkGhUODAgQMGty1evBgKhQIXL160KFZjjh8/jo4dO6JUqVLw9PREy5YtsWvXLqP7Xr9+HX379oWfnx/c3NxQqVIlDBgwAFlZWQDEj/fkyZPx2WefAQBCQkKgUCigUChw+PBhHDt2DAqFAuvWrTM4x5o1a6BQKHDmzBmTMeeVkCxZsgRXr17Fjz/+CHd393zLT4g1UEJCSBE7ffo0kpOT0b59e4PbLl++jNq1a8PFxUW03diXh7+/P2rVqmX0i0+hUODll1+2buB6evXqhRo1amDz5s0YP348fv/9d4wZM0a0z9WrVxEWFobLly/jxx9/xM6dO9GtWzeMHj0aU6ZM0e4XHx8PHx8fzJgxA3/99RcWLlwIFxcXNGvWzGSTQs+ePVGtWjVs3LgRS5YsMbrPa6+9Bl9fX6xcudLgtlWrVqFJkybax9bcWPUdOXIEHTp0wLNnz7B8+XKsW7cOpUqVQvfu3bFhwwbRvv/++y/CwsJw6tQpTJ06FXv27MH06dORlZVltC/HsGHD8NFHHwEAtmzZgpMnT+LkyZNo0qQJ2rRpg8aNGxtNmBYsWICwsDCEhYWZjLtcuXLw9/c3SEiePHmCyZMno2PHjgY1eITYFCOEWMXAgQNZ5cqVDbZPmjSJCd9q33//PQPAEhMTDfatXr0669y5s8H2+Ph4BoBNmzZNtP3dd99lfn5+Bvs7OzuzDh065BvzypUrGQB25syZfPeJjo4WlWfmzJmi/UaMGMHc3d2ZWq3WbuvcuTOrWLEie/bsmWjfUaNGMXd3d/b48WOj58zJyWHZ2dmsevXqbMyYMaLbNOf/+uuv8y0fY4xFREQwDw8P9vTpU+22q1evMgBs/vz5Fseq/3g0b96c+fr6stTUVFH89erVYxUrVhQ9Hh06dGDe3t4sKSnJZLz6x//hhx9E68b2jYqK0m77559/GAC2evXqfB+b8PBwVrVqVdG20aNHMxcXF3b58mXRdrVazUqVKpVn7IQUBtWQEFLE4uPjoVAoUK5cOaO3C5t38rvN19cXSUlJyMnJEW3Pyckx2kxhTa+//rpovUGDBsjMzERSUhIAIDMzEwcOHMCbb74JT09P5OTkaP+6du2KzMxMnDp1ShvvtGnTUKdOHbi6usLFxQWurq7477//cO3aNaPn79Wrl1lxDhkyBBkZGaLaipUrV8LNzQ39+vWzOFahtLQ0nD59Gm+99RZKliyp3e7s7Iz+/fvj/v372hqe9PR0HDlyBG+//TbKly9vVuz56du3L3x9fUW1JPPnz0f58uXxzjvv5Hv/+vXrIzo6WtsH58aNG1i8eDFGjhyJunXriva9desWfHx8rBY7IfooISGkiGVkZECpVMLZ2dngNh8fHyQnJxtsf/z4MQCgbNmyou3u7u5gjCEzM9M2webBx8dHtK7phJmRkQEASE5ORk5ODubPnw+lUin669q1KwDg0aNHAICIiAh89dVX6NGjB3bs2IHTp0/jzJkzaNiwofZ4+sy96qdu3boICwvTNtvk5uZi7dq1eOONN7SPpyWxCj158gSMMaOxBAYGao+t2Tc3NxcVK1Y0K25zuLm54YMPPsDvv/+Op0+f4uHDh/jjjz8wbNgwszrFNmjQAGq1GlevXgXAnwdvb29MnjzZYN+oqCg0bNgQQ4YMgZeXF1566SVER0dbrSyEuOS/CyHEHO7u7tqOiUL6X2TlypVDdnY20tLSUKJECdFt9evXx7p165CTkyPqR6Lp3FmvXj3R/o8fP4abm5vo17m9KFOmjLamYOTIkUb3CQkJAQCsXbsWAwYMwLRp00S3P3r0CN7e3kbvm1dNkr7BgwdjxIgRuHbtGu7cuYOEhAQMHjy4QLEKlSlTBk5OTkhISDC4LT4+HgC0NWFly5aFs7Mz7t+/b3bc5vjwww8xY8YMrFixApmZmcjJycHw4cPNuq+wb1JycjJ2796NZcuWGX3Mo6KicPLkSaxfvx5LlizBkCFD8NVXX2Ht2rXWLA4pxighIcRKgoODkZSUhAcPHsDPzw8Av6Jm7969ov1q1aoFALh9+7b2C0HjzTffxLJly7B582ZRlfvq1asRGBiIZs2aifa/c+cO6tSpY4viFJqnpyfat2+PqKgoNGjQAK6urib3VSgUBr/od+3ahbi4OFSrVq3QsfTt2xcRERFYtWoV7ty5gwoVKiA8PLxAsQqVKFECzZo1w5YtWzBr1ix4eHgAANRqNdauXYuKFSuiRo0aAAAPDw+0a9cOGzduxHfffWeyyU6ffs2TvoCAAPTu3RuLFi1CdnY2unfvbva4IZoO1BcuXMAPP/yA0NBQDBkyxOi+UVFRmDhxorYz9oABA/D555+bdR5CzEEJCSFW8s477+Drr79Gnz598NlnnyEzMxPz5s3Tjh2iobn65dSpUwYJSZcuXdCpUyd8+OGHSElJQbVq1bBu3Tr89ddfWLt2raiZR61W459//sHQoUMNYnFxcUG7du3M7kdy8OBBoyOPaporCmru3Llo3bo12rRpgw8//BDBwcFITU3FrVu3sGPHDhw8eBAAvxpm1apVqFWrFho0aIBz587hhx9+sFrzhre3N958802sWrUKT58+xdixYw0uuTY3Vn3Tp09Hp06d0L59e4wdOxaurq5YtGgRLl++jHXr1olqcmbPno3WrVujWbNmGD9+PKpVq4YHDx5g+/bt+Pnnn1GqVCmD49evX18b38CBA6FUKlGzZk3Rvh9//LE2WTV2RZEpbm5uqFGjBpYuXYrMzEz8/fffBo+LRlRUFJYuXapdf/jwoUGzHSGFInWvWkIcye7du1mjRo2Yh4cHq1KlCluwYIHBVTaMMdamTRvWtWtXo8dITU1lo0ePZv7+/szV1ZU1aNCArVu3zmC/AwcOMADs3LlzBrcBYO3atcs3Xs1VGqb+oqOjTV5l8/DhQ6PH0r8aJDo6mg0ZMoRVqFCBKZVKVr58edayZUv27bffavd58uQJGzp0KPP19WWenp6sdevW7NixY6xdu3YG5TB1/vzs27dPW66bN28a3cecWI2V89ixY6xDhw6sRIkSzMPDgzVv3pzt2LHD6DmuXr3KevfuzXx8fJirqyurVKkSGzRoEMvMzDR5/AkTJrDAwEDm5OTEALBDhw4ZHDc4OJjVrl3boseEMcb69OnDALD+/fub3CcuLo4BYOnp6dptb731Fps1a5bF5yPEFAVjjBVpBkQI0TbJ3Lt3DxUqVCjQMfr37487d+7g77//tnJ0RG4uXryIhg0bYuHChRgxYoTVj79r1y706NEDv/zyC959912sWbMG06ZNQ1RUlNFaHUIKghISQiTAGEPLli0RGhqKBQsWWHz/27dvo3bt2jh48CBat25tgwiJHNy+fRv37t3DxIkTERMTg1u3bsHT09Pq5/n222+RkJCA6OhonDhxAqGhoVi2bBmqVKli9XOR4osSEkIkcvnyZWzfvh3jx4832W5vyqFDh/Dff//h/ffft1F0RA4GDRqEX3/9FbVr18bPP/+MVq1aSR0SIQVGCQkhhBBCJEcDoxFCCCFEcpSQEEIIIURylJAQQgghRHI0MFo+1Go14uPjUapUKYuGqiaEEEKKO8YYUlNTERgYmG/nfUpI8hEfH4+goCCpwyCEEEJkKzY2Nt+RlykhyYdm0J/Y2Fh4eXlZ5ZgqlQr79u1DeHg4lEqlVY5pTxy5fI5cNoDKJ2eOXDaAyidXKSkpCAoKMmsAPUpI8qFppvHy8rJqQuLp6QkvLy+HeuFpOHL5HLlsAJVPzhy5bACVT+7M6fJAnVoJIYQQIjlKSAghhBAiOUpICCGEECI5SkgIIYQQIjlKSAghhBAiOUpICCGEECI5SkgIIYQQIjlKSAghhBAiOUpICCGEEAtFRgKdOgG//QZERwOhocCbbwJZWVJHJl+UkBBCrIIxqSMoeqdOAX37Anv3Sh0JKWojRgD79wPvvccTkfPngW3bgPnzpY5MvighIYQUSm4u0L07UKUKcPGi1NEUjf37gXHjeLnXrwd69wYyMqSOithSUhJw9y5PvBMTgVu3dLf9+69uecmSIg/NYVBCQogDSkgA2rfnv97S0217ro0bgZ07+Yf1hx/mve/du8DBg4BardsWFwe89RYwa5b1a1kePwbu3zd+G2PA8+fAs2c8ptRU4/tdvQosWwZcuQKcOwf4+vKq+h9+AB494vukpgJ//mnd2AtLpQIuXAD27QN+/hkYMABYtUrqqOTpzh0gJIT/OTkBAQGm9713D8jOzv+YZ84AzZoBX39dPGsXjaGEhBCZYQxYu5bXSAwYAKSlGe4zZQpw+DBv3y5RAvjvP9vFc+aMbvnECdP7PX0KNGwIdOwILF2q2/7RR8DmzcBnnwGDB/MkYcUK4MYNy+JITQXWrQNq1QIGDgSGDQN8fICgIEChAM6e1e2rVvM4SpUCvL35spcX0LIlMHIk8OQJkJPDa0KaNgXefx+oV48vP3xo/Pwffsjve/o0Xz95kicC5nw5mRIZCbzxBv9viVOnAFdXoHFjoHNnYPhw4Ndf+eMbHs4T1UGDeN8HY548AZKTgUOHeOJVnGt/VCqgalXzE/ucHP6eUKt5QqxSGe6TnQ1MnAj88w/wzTeUKGoxkqdnz54xAOzZs2dWO2Z2djbbtm0by87Ottox7Yncypeba/6+9lC2DRsY42kJ/5s5U3z78+fi2wHGWrViLDMz/2MXpHwDBujO4+LCmFrN2H//8f937jAWFsZYxYr8NmFMjDGWnGwYq7c3/+/uztipU+bFsGcPY6VKGR5L+OfkxNjmzSq2bds2dvZsdp77DhvG2NixeR/P1J+bG2P79jFWogRff+894zFnZDC2axdj69czFhdneLtKpTtmlSrGjxEby1j79oy9/TZja9ao2OrVu1lcXDZTKMyLNTiYv16E1qzhj71wv3feMe95KKyUlLxuy2Y//7yPZWdnsw0bGPvhB93+N24wdvWqbWJatapgrwPNX4kSjD18qDve5cuM+fuL9wkLs4/PFluw5DuUEpJ8UEJiOXsu39OnjB07pktCduxgrEwZxho35rflpyjKlp3N2NSpjPXvz1hSkuHtL79s+KF3+7bu9gkTjH8wDhpkzrktL1+jRrpz+PkxNnw4Xx44kLHOnU1/UJ86xdi2bXl/mL/xhunzqtWMjRhh2ZdD06a5bNu2bWzpUlWhvmQs/Tt7lrG7dxl7/33G/viDxz9kiO52X1/GPvqIf3m1acO/XPftEx/jyRPGYmL48zttGi9//fqG53J3V1sU24IFjJ05w5Oj06eZyWSmYUPGrl9nrHlzxkJCGDt50vA5uXaNl7FTJ8b27mUsOpqxgwcZy8rK/3X05Zf8PB9+aHhbTg5jLVrkMoCxRo105atene8P8LiNxWTMnTuMNWvGH++VK/lzc+IEP4/G6dOMrV3L2KhRusegRg3+PFy8yBOihASeDI0ezRNRU4/xrFmMbdrEH5969Yzvc+uW/X5uFgYlJFZECYnlbFm+27d5EpHXoePjxR8smZmMbdzIf002b87f/N27M/brr+IPhP79+QdoXoyVLTubsfPnGbtyhbG0NMaiohgbM4ax5cv5l8auXYx98AFjCxfydcb4B9PChYw9eiQ+flYWY126iONauFB3e1KS6S+MgQMZi4jQ1US4uvIPVE9P3T765zOnfHm5fVscQ361FJb+lSpl+rk+d868Y3z7rXj9gw8usA8+yNGuf/MN/2IrX978uL78kn+xhIczNmNG/vu/8474i2jqVMY8PEzv7+PDWJ064m0zZ+Z9H2N/o0fz1+T+/Yw1aKDb/uqrhX9uvL3FtYsnT5r+Uh46VPzc3bjBE7JRo3hNkbA2CGDs8WPx/qdOmReTsWTGmE8+Ed9P87i2bcvYkSM8XmPHN1aTpaFW62rFCvJXpoyabd7seN8LlJBYESUklrNW+dLTeXKh+RJ/9ox/UAOM1azJf8EI5eYy1qcPv71qVf5rTq02/ILP78/Pj7G5c80vm+YXWkH++vbVHfvvv03vd+wY38eS6uPRow3jO35cd77Ll/mv3qFDdY+xpc/d+vWF/2LT/H31lfHthw/zBK9XL3FC9eOP4v3c3PhrJCmJN+GMHMnY/Pm8bPpJiebP2ZnfR+Obb8S3h4TwxEet5l9UPXrwX8Yqle4+9++Lkz57+QsJET9XOTm8piYhga+/8orp+1auzFjr1vmfo04dxsaNY2zKlPwfgz//1MXSrFn+x37/fV0CYOq1of/n5cWTjTff5O8ZtZr/UNA07Vy6xB+DDh0sfzxLlNC9T0wx9Toz9y8i4ozDfS9QQmJFlJBYzhrlE/aTcHVlrF8//uWi/waOjeX7p6cb1njUr8/Y998X/MPh2jV+7O3b+S/atDTDsj19WvgvjuHDeWKQ334bN/KmJc36uHF57799O49/3jzdttatdY+xprYIYOzo0YI9dz//XPjyA7yKPyPD+BeV8Ffnxx/z86rVjDVtqtveuDFjN2+ajjMzk7HXXzc8tvDx0LyOJkzgzRgPHuT/BaRx4gRjS5fyvgJeXtZ5TAr7FxGRd8ynTplOIqZP1+139ar1YlqwgCdE5u7/1luM3btnuN2cPjLu7uJk3JwkKK+/Jk3yfx1kZ/PXz5AhPAn64gvjx2renPfdiY3V3x7HMjIc63uBEhIrooTEcuaUT63mzSOvvsprMJ484dvv3WOsd2/LPigCAgr3QTNvnvFjzJ/Pf105O/P1fv0YO38+m7322i12/LiKPXvG2GefFd0XjPAvNFT3ZblsmfEq+AcP+O1794q3b9rEm4aE26ZNM/+5E/rhB+uUZ9s2frysLMb++osng05OxveNjeVV65r1atXMSxzS0hjr3j1XdCxhc5i1rF7NO4t+9BE/vvB8U6aIvyQnTWJs8WK+rOkM+/HH4vu89ZZ43cWFsW7d+Pbt28W1VF99dYJNnpzDli7Nu1lTIzWV1xqMHCk+x8GD4v2E/V00cZt6fho3Zmz8eJ6snzwpvi2vfhbG/lxdxetVqjxhqanZLCWFl2/xYsZWrOC1VMb601jy17Fj3rfv32/5ayE+njGlUnyc9u15s67w9aJ/rrfesvxc9ooSEiuihMRy+ZXvwQP+har/Jpw40fDNa4u/du34B3m1ajyhyM1l7MIFw/3Cw3lTQUHOMXkyY59+avp2TdOTsT+Fgn9ItWnDOzsa22frVsPH9dQp3RUqY8botutfydK0qeEXxeuvm/fc6TO3Kl3zZaRJPPX7DBjrUDx5snnHXbXKrFC15Vu3bgc7fTqb7dwp7mtkC5mZjNWqxeNs0oR/iaan89qt6dP5+dVq3sSkqZG7fl1XA9CvH6+h0Fz14uHB2O7d4nOo1fzKmN9+UxX4cyU3l7HBg3ny3by5YTJz5Yqu5kfTT2PJEt4s1KgR73/VsCHvZKz/mO7YYd7zGBTEm+eGDjVdczN06EWT5UtL402tffua/5r8/nvGfvqJN7WoVDyBCA7WfU506cJYy5a82a6gVqzgP3hatdLV6Or7/HPD2EztKzeUkFgRJSSWy6985l5O2bAhrwbX1FAIv7Dz6rdRv774HA0aMHbgAG9bbtqUsX/+MR53bi7/8C9Ix0ylkrdNb9mi6+iXk8OvbKlRg3+gLVvGPzCzsvg++v0VAB7j+fPiuJYsEe8zYIDpS5UfP+Yfqvr0Ey7hlQOaBEmttvy1qf9rPq+/EyfE99VcDaTf4VH4fBi7okj4t2SJWWFqSfHee/CAdy625CPk9995U57mS+n8ecZ++42xxETT97FG2TQJkjEPHvAazIKIizPelDV/Pv/CTkoSJ0F37oibJwHGxo3LYVu2mFe+997L+3UzYQJjmzcbL6taLe67VhQePmSscWPx1VHmXvJu7yghsSJKSCyXV/nM6S0/fLj4gzc9nV/uGBTEq3C3b+e/hnr0YOyll/gvogMHdFe3/Psv/2U6fTrvd2Gp2bMtT0h69SrYYzVoEL9/7dq8TMakpPByurnxjqoF/aDM72qQzZstf20OHmze42Mq6cjvqp+0NJ6Uai7NbNNGd0xhh2BzOfJ7z97L9s8/uiuZnJ3NawJJS+PJ9L17lpVP2Pm7Rg2e2GmaNTWdve1NdnY269PnmjZuY7WgcmTJd6hLUQ/ERooXtZoPYx4YyCefatVKfHurVnxeiNu3+Wiav/8O9Okj3sfDg4+2ee0aHy2xfHm+fetWw/M1aqRbHj++YDGPGsWHQz95kq+3bMljvHMHCAhgSEhQaPf94QceW9euBTvXokV8HpSXXgI8PY3vU6oUH/2TMf4YFdSHHwIzZ/LRI4359ls+N4slUlJ0y2+8YXr49CpVjG/38cn7+J6ewP/+p1s/cABYvJiPQjpokEWhEomFhfH5X27e5CPIOjvnfx9PTz66L2B8xFNT+vXj79/0dP4e9fMD9uzh72N//4LFXxR8fHRD4iYkSBiIRCghITbBGPDTT074/HO+Xro0nzNEqGFD4PhxPr/JtGlAly581kxTSpTgf7amVPIJ0/r0AVxc+LKTE3D5MtCmTQ4+/PAGHj2qg/fec8LbbxfuXB4e5iczhUlGAD40eufOfHh1jQoV+KRhKhWfGE84dbpazc+Z13mFCcmnn5pOSEJCChe7hlIJjB5tnWORouflxYfftzWl0vgkd/acjABAmTKZ2uXERAkDkQjNZUMsdv48/zX866/Gb2cM+OGHpvj8c91PIP1kBNB9SQUH87lN8kpGilqlSnxelqNHee2Ovz/wyis8MXnjjdvYvDm30MmIFDp2FK+7ufEaGoDP2quZ8yY5mc8JExJier6T+HjxHCutWvHkskIFw31N1ZAQQnTKltX9IiiONSSUkBCLDR8ObN/OJ3bbu5fPbjl8OJ/MLDUV+P57J5w4YeRbSU/r1kUQLBF57z3xeokSQO3auvV//uHVIevWOeG///hzO3Cg4XFyc/kspUJOTkDlykBsLJ+MrWVLvr1sWaBuXSsWghAHJawhKY4JCTXZEIskJIhnd/3lFz59vKa/xerVgFotznMnTwaGDuUzuJ44wZs+OnfmfTVI0XJz4+349eoBmZk8qfD21t3+8cfOeP/9Snj2TNdOc+wYb75xevG0qtU8mTx1Sne/smV1ywoF4O7O+3vs3AnUrw+ULGnbchHiCLy8suDkxKBWKyghISQ/8+aJ1/fu5bUiGjk5AMC/zF59VY1Nm5y0/T70f1ETaVStCkRFAQ8f6mqpOnXizS9ZWQosXNgQNWuKO44kJOiaYv77T5yMADzZ1OfuDrz1lg0KQIiDcnbmHXATEopnDQk12RCL6PcbESYjQq1axWHr1twi6YRKLFerFtCmja7T6vr1utvUaidcuyZOSG7f1i3rd7b77DPep4gQUniajrcPHvCm0eKEEhJitowM3jyTl9q1gTVrcvDpp2fNuqyP2IeyZYFdu0zf3q4d8OOPfFk/IdHvl0IIKbiAAAaAJyOPHkkcTBGjhISY7e5d3fK77wITJohv37gRuHoV6NOHafsbEPlo2zbv28eOBf75R1yV/MYbQIMGto2LkOJEeGny/fvSxSEF+togZrtxQ7ccEsITkjJl+Hq1asBrr0kTF7GOkiWBc+fyHn1q/XpxQkJjghBiXdWqMe3ylSsSBiIBSkhIvhjjv4SF44SEhPARRPfsAT7/nF9R4e4uXYzEOurXz/v28+fFTTb2PtAUIXLToIEuIfn3XwkDkQAlJCRf//3Hxx0RqlWL/2/WDJgxgw8kRhzDmDHnTN527564XdvXtwgCIqQYqV9fl5BcvChhIBKghITkSzg8uAYNdOW42ra9jz/+yMHevYa3xcWJ58IRjmFCCCk8f3/d+0ozcnJxQeOQkHw9eSJe9/Hhc9MQx6RQAD16MCiVhrepVLq+RCVL8rl+CCHWo1DwPnlnzwIxMXx+KTc3qaMqGrKpIZk+fTrCwsJQqlQp+Pr6okePHrgh7GVpwpEjRxAaGgp3d3dUqVIFS4zNuES0bt3il3GuWaPbpj87rGb2TVI8aRJUTYdmQoh1VavG/zNmei4pRySbhOTIkSMYOXIkTp06hcjISOTk5CA8PBxpaWkm7xMdHY2uXbuiTZs2iIqKwsSJEzF69Ghs3ry5CCOXl759gd9+4/OXPHzIt+nXkKxcWfRxEftDzTWE2IYmIQHEVzc6OtlUuP7111+i9ZUrV8LX1xfnzp1DWxMDKCxZsgSVKlXCnDlzAAC1a9fG2bNnMWvWLPTq1cvWIcvS2bO65fv3gfLlxTUkv/5KHVgJRzUkhNhGvXq65aio4jMSsmwSEn3PXsxnX1Y4q5eekydPIjw8XLStc+fOWL58OVQqFZRGGsmzsrKQlaWbAjrlRY9OlUoFlSrvMRrMpTmOtY5nXbrH5MmTHKhUDI8eOQHgw65WqMC35cW+y1c4jlw2wFj5jHQkecHLSw2VSl5jWzvy8+fIZQOKV/l4szh/7505I7/3mZAlz5csExLGGCIiItC6dWvUE6aSehITE+Hn5yfa5ufnh5ycHDx69AgBAQEG95k+fTqmTJlisH3fvn3w9PQsfPACkZGRVj1eQT196oabN73RsOFDAN212yMjzyM1NQH//tsYAK8WuXz5KFJSTExgo8deymcLjlw2QFe+jz6qhPnzG6NGjcdITCyBlBRd77q0tPvYvTtKqhALxZGfP0cuG1A8yscY4OnZFenpSpw9m4Hdu/dLHVaBpaenm72vLBOSUaNG4eLFizh+/Hi++yoU4knCGGNGt2tMmDABERER2vWUlBQEBQUhPDwcXl5ehYhaR6VSITIyEp06dTJaS1OU1GqgYUMX3LihQK1a4pqPypWbIDyc4eOPdS+Tt95qg3Ll8j6mPZXP2hy5bIBh+bp2BcaOVcHXtxRu3xZXJdevXwFduxom9fbMkZ8/Ry4bUPzKV6mSC65fB9LSPNG1a1epwyuwFGPjRpggu4Tko48+wvbt23H06FFUrFgxz339/f2RqDcTWFJSElxcXODj42P0Pm5ubnAzco2VUqm0+pvAFse01J07uk5T16+Lk7SnT11w/DgfDAsAOncGAgLMj9ceymcrjlw2QFw+TZ+hOnXE+zRs6AylUp4zKDry8+fIZQOKT/k0P/zS0hRQq5WyvfTXkudKNlfZMMYwatQobNmyBQcPHkRISEi+92nRooVB9d6+ffvQtGlTh35BWyKvuRIePQJ27tStDxli+3iI/dKvVGzdWpo4CCkOhDXRycnSxVGUZJOQjBw5EmvXrsXvv/+OUqVKITExEYmJicjIyNDuM2HCBAwYMEC7Pnz4cNy7dw8RERG4du0aVqxYgeXLl2Ps2LFSFMEu5ZeQ7NjBl11ceA0JKd6GDeP/GzQAqleXNhZCHJmwEp8SEjuzePFiPHv2DC+//DICAgK0fxs2bNDuk5CQgJiYGO16SEgIdu/ejcOHD6NRo0b45ptvMG/ePLrkV+Cc6WlLcPiwblCetm1pdFYCzJvH5zWKjDSsMSGEWE9xTEhk04dE0xk1L6tWrTLY1q5dO5w/f94GEckfY8CJE6Zv1/QdAYDXXrN9PMT+eXgA3bvnvx8hpHCKY0IimxoSYn337wPx8fnv5+YG9O9v+3gIIYRwwoREOMO2I6OEpBi7ft28/Zo0Qb6X+hJCCLGeoCDd8q1b0sVRlCghKcaEU1svXQr8+y/wzTeGnRWrVi3auAghpLgTjvlz6ZJ0cRQl2fQhIdZ386ZuuUYNfuVEgwZ8Mr3Zs3W3mXGFNSGEECsKCADKluVziRWXhIRqSIoxYQ1JjRq6Zf3xRighIYSQoqVQ8B+IAO/rZ05/P7mjhKQY09SQlCwJ+PvrttetC/z2G7+iomxZoFs3aeIjhJDirGVL3fLff0sXR1GhhKSYUql0Y4xUr244pkS/fjwjv38f8PUt+vgIIaS4a9VKt3zqlHRxFBXqQ1JMXb0K5L6Y0drUiJve3kUWDiGEED1NmuiWL16ULo6iQjUkxdT8+brl+vWli4MQQohxfn5A+fJ8ef/+vEfWdgSUkBRTR4/qlv/3P+niIIQQYpxCIR52YdYs6WIpCpSQFFMPHvD/1avzLJwQQoj9EY6S/fSpZGEUCUpIiqHMTCAlhS9TMkIIIfZLWIOt+dx2VJSQFENffKFbpoSEEELsl1IJuLvz5dRUaWOxNUpIiiHhKKw0Rw0hhNg3Ly/+n2pIiEPRf0HHxUkTByGEEPNQQkIc0v374vV335UmDkIIIebRJCSpqQBj0sZiS5SQFDP6Ccmbb0oTByGEEPOUKsX/5+TwixIcFSUkxYwwIVm4EHBzky4WQggh+dPUkACO3bGVEpJiRjhjZIUK0sVBCCHEPMKExJH7kVBCUoxkZQG7dunWNUMSE0IIsV+aJhsAePZMujhsjRKSYkKlAho2FM8YSZf8EkKI/fP31y3r9wN0JJSQFBOXLwM3boi3+fhIEwshhBDzVaumW/73X+nisDVKSIoJYd8RDW/vIg+DEEKIhapX1y1PmgQkJEgXiy1RQlJMGEtInJ2LPg5CCCGWEdaQAMCOHdLEYWuUkBQTxhISQggh9q9sWcDFRbd+5Yp0sdgSJSTFAGPA5MlSR0EIIaSg7t7VLV+7JlkYNkUJSTEgvLJGY9Kkoo+DEEJIwQQG8poSALh+XdpYbMUl/12I3J09K14/fx5o1EiSUAghhBSAQgEEBwOPH/Mm+JwccTOOI6AakmLg6lXd8t9/A40b8xc3IYQQ+ahYkf/PzQUePJA2FlughKQYECYkdepIFwchhJCCCwrSLcfGSheHrVBCUgzExfH/ZcrQ2COEECJXmhoSwDFHbKWEpBh4/Jj/p5FZCSFEvighIbKWmws8fcqXNT20CSGEyI+wyYYSEiI7z57xcUgASkgIIUTOhDUkjtiHxMEuGiJCMTHAunW6dUpICCFEvipU0C07Yg0JJSQOKicHaNdOPLofJSSEECJf7u5A+fLAw4eOmZBQk42Dun1bnIwAlJAQQojcaZpt4uKA7GxpY7E2Skgc1I0bhtsoISGEEHnTjCWVmwtcvChtLNZGCYmDMpaQlCtX9HEQQgixntBQ3XJYmO6iBUdACYmDunXLcJufX9HHQQghxHqaNROvO9LVNpSQOKhHjwy3UUJCCCHy1qKFeD0tTZo4bIESEgf15InhNn//oo+DEEKI9SgUwIcf6tYzMqSLxdooIXFQmuHihWjoeEIIkT9PT90yJSTE7hlLSJzo2SaEENnz8NAtp6dLF4e10VeUg9JvsnnzTWniIIQQYl3ChMSRakhsOlLrs2fPsHXrVhw7dgx3795Feno6ypcvj8aNG6Nz585o2bKlLU9fLDEGXL0KPH/O16tWBSZPBrp1kzQsQgghViJssqEaknwkJCTgf//7HwICAjB16lSkpaWhUaNG6NixIypWrIhDhw6hU6dOqFOnDjZs2GD2cY8ePYru3bsjMDAQCoUC27Zty3P/w4cPQ6FQGPxdv369kCW0Xx9/DNSrp1uvXRt47z2gTBnpYiKEEGI9VENigYYNG2LAgAH4559/UE/47SiQkZGBbdu2Yfbs2YiNjcXYsWPzPW5aWhoaNmyIwYMHo1evXmbHc+PGDXh5eWnXy5cvb/Z95SQ3F5g/X7yNRmclhBDHQgmJBa5cuZLvl76Hhwf69u2Lvn374uHDh2Ydt0uXLujSpYvF8fj6+sLb29usfbOyspCVlaVdT0lJAQCoVCqoVCqLz22M5jjWOp7Gv/8CgFK0rXHjXKhUaqueJz+2Kp89cOSyAVQ+OXPksgFUPiFXVwU0X9+pqUX/GW8JS54vmyQkltZA2LrGonHjxsjMzESdOnXw5Zdfon379ib3nT59OqZMmWKwfd++ffAUNtxZQWRkpJWPVwlAY9E2T88D2L1bmhTa2uWzJ45cNoDKJ2eOXDaAygcAV674AWgOAPj335vYvfumjaMquHQLOrnYtFMrAKxevRrlypVDtxe9KseNG4elS5eiTp06WLduHSpXrmyzcwcEBGDp0qUIDQ1FVlYWfv31V3Ts2BGHDx9G27Ztjd5nwoQJiIiI0K6npKQgKCgI4eHhomafwlCpVIiMjESnTp2gVCrzv4OZTp8WdwkqWZJh8GDTyZet2Kp89sCRywZQ+eTMkcsGUPmEPDwU2uWgoBro2rWarcMrME0rgzlsnpBMmzYNixcvBgCcPHkSCxYswJw5c7Bz506MGTMGW7Zssdm5a9asiZo1a2rXW7RogdjYWMyaNctkQuLm5gY3NzeD7Uql0upvAmsfMy5OvH7woELSN64tHjN74chlA6h8cubIZQOofAAg/G2cleUMpdLZxlEVnCXPlc0TktjYWFSrxrO3bdu24a233sL777+PVq1a4eWXX7b16Q00b94ca9euLfLzFoWYGN1ycjJ1aCWEEEfkqJ1abT4wWsmSJZGcnAyA98N45ZVXAADu7u7IkOCRjIqKQkBAQJGftyhoEhJvb0pGCCHEUTlqQmLzGpJOnTph2LBhaNy4MW7evKntS3LlyhUEBwdbdKznz5/j1q1b2vXo6GhcuHABZcuWRaVKlTBhwgTExcVhzZo1AIA5c+YgODgYdevWRXZ2NtauXYvNmzdj8+bNViufvVCpdNNQV6okbSyEEEJsp2RJ3fKzZ9LFYW02T0gWLlyIL7/8ErGxsdi8eTN8Xszwdu7cOfTt29eiY509e1Z0hYym8+nAgQOxatUqJCQkIEbQbpGdnY2xY8ciLi4OHh4eqFu3Lnbt2oWuXbtaoWT25fZtnpQAfDA0QgghjsnPD3B1BbKz+We/o7BZQrJ06VK8/vrr8Pf3x4IFCwxuN3ZpbX5efvllMMZM3r5q1SrR+rhx4zBu3DiLzyNHV6/qlikhIYQQx+XsDFSpAly/zhMStdoxJk+1WRHWrVuH4OBgNGvWDNOmTcNV4TcmsTrhaPiUkBBCiGOrXp3/z8w0vMJSrmyWkBw6dAgJCQn46KOPcOHCBbRo0QJVq1ZFREQEDh8+DLXafkeWkyPhFTZVqkgXByGEENurUUO3fOKEdHFYk00recqUKYP33nsPf/zxBx4+fIiFCxciMzMT/fv3R/ny5TFgwABs2rQJaWlptgyjWBBmyBUqSBcHIYQQ2xPOorJxo3RxWFORtTq5urri1VdfxaJFixAbG4u9e/ciODgY33zzDWbPnl1UYTikR4+AnTv5sosL4OsrbTyEEEJs6+WXdbO4Hz8O5NG9UjZsfpWNKU2bNkXTpk0xdepUh50sqahMnapbzsnhHZ4IIYQ4LmdnIDQU2L8fePAAiI+Xf+24zRMSxhg2bdqEQ4cOISkpSdR3RKFQYPPmzQ49DHBRmD9f6ggIIYQUNU1CAgDnzsk/IbF5k83HH3+M/v37Izo6GiVLlkTp0qW1f9aarK440+9dPX68NHEQQggpWqGhuuVz56SLw1psXkOydu1abNmyxSEHI7MHhw/rllu2BL79VrJQCCGEFKGmTXXLZ89KF4e12LyGpHTp0qhC16HazKFDuuVvvqH+I4QQUlwEB+s6tp46pRutW65snpBMnjwZU6ZMkWQiPUeXmwvs2MGX3d2B5s2ljYcQQkjRUSiAmjX58uPHfFLVM2ekjakwbN5k07t3b6xbtw6+vr4IDg426MB6/vx5W4fgsHbuBJKS+HLXroCnp7TxEEIIKVohIbx2BACePwd++w0IC5M2poKyeUIyaNAgnDt3Du+99x78/PygUChsfcpiY9o03fLAgdLFQQghRBply4rXnz+XJg5rsHlCsmvXLuzduxetW7e29amKlZgY4J9/+HL9+kD37tLGQwghpOjpX6yamSlNHNZg8z4kQUFBdHmvDezdq1vu3Zu3JRJCCClePvhAvE4JSR5+/PFHjBs3Dnfv3rX1qYqVCxd0y23bShYGIYQQCVWuDFy8qFuXc0Ji8yab9957D+np6ahatSo8PT0NOrU+fvzY1iE4pEuXdMv160sXByGEEGkJR9aQ8wWtNk9I5syZY+tTFEtXrvD/FSoYdmoihBBSfLi56ZaphiQPA+nyD6vLzubXnAN8YBxCCCHFl4sL/8vJkXdCYpM+JGlpaTbdv7h79Ei3XL68dHEQQgixD+7u/D8lJHqqVauGadOmIT4+3uQ+jDFERkaiS5cumDdvni3CcFjChKRcOeniIIQQYh88PPh/OSckNmmyOXz4ML788ktMmTIFjRo1QtOmTREYGAh3d3c8efIEV69excmTJ6FUKjFhwgS8//77tgjDYVFCQgghREhTQ0KdWvXUrFkTGzduxP3797Fx40YcPXoUJ06cQEZGBsqVK4fGjRtj2bJl6Nq1K5ycbH7lscOhhIQQQoiQIzTZ2LRTa8WKFTFmzBiMGTPGlqcpdh4+1C1TQkIIIcQREhKqnpAhSkgIIYQICfuQMCZtLAVFCYkMCQe9DQqSLAxCCCF2QlNDwhgfGkKOKCGRoVu3dMtVq0oXByGEEPugSUgA+TbbUEIiQ//9x/8HBgIlSkgbCyGEEOlRQkKK3PPnQFISX6baEUIIIYCuDwnAvyfkyOYJSXBwMKZOnYqYmBhbn6pYePJEt+znJ10chBBC7EeFCrrle/eki6MwbJ6QfPrpp/jzzz9RpUoVdOrUCevXr0dWVpatT+uwUlN1y6VKSRcHIYQQ+1Gtmm759m3p4igMmyckH330Ec6dO4dz586hTp06GD16NAICAjBq1CicP3/e1qd3OMKEpGRJ6eIghBBiP4QJifDCBzkpsj4kDRs2xNy5cxEXF4dJkybhl19+QVhYGBo2bIgVK1aAyfXC6SJGNSSEEEL0OUJCYtORWoVUKhW2bt2KlStXIjIyEs2bN8fQoUMRHx+PL774Avv378fvv/9eVOHIFiUkhBBC9AUFAUoloFJRQmLS+fPnsXLlSqxbtw7Ozs7o378/fvrpJ9SqVUu7T3h4ONq2bWvrUBwCJSSEEEL0ubgAISHAzZu8DwljgEIhdVSWsXlCEhYWhk6dOmHx4sXo0aMHlEqlwT516tRBnz59bB2KQxBezkUJCSGEEI1q1XhCkpYGPHgA+PtLHZFlbJ6Q3LlzB5UrV85znxIlSmDlypW2DsUhUA0JIYQQY4RjU92+Lb+ExOadWtu3b4/k5GSD7U+fPkWVKlVsfXqHQwkJIYQQYypV0i3fvy9dHAVl84Tk7t27yM3NNdielZWFuLg4W5/e4VBCQgghxJiKFXXLckxIbNZks337du3y3r17Ubp0ae16bm4uDhw4gODgYFud3mGlpOiWaRwSQgghGsLRWuX4e99mCUmPHj0AAAqFAgMHDhTdplQqERwcjB9//NFWp3dYwiGBAwKki4MQQoh9oYTEBLVaDQAICQnBmTNnUK5cOVudqli5eZP/9/EBypaVNhZCCCH2IzBQt0wJiRHR0dG2PkWxkZame5HVqCFtLIQQQuyLuzvg5cWb9h89kjoay9kkIZk3bx7ef/99uLu7Y968eXnuO3r0aFuE4JCuX9ctV68uXRyEEELsU5kyPCF5+lTqSCxnk4Tkp59+wrvvvgt3d3f89NNPJvdTKBSUkFjgn390y02aSBcHIYQQ++TtzfsaPnkiv9FabZKQCJtpqMnGek6d0i23aCFdHIQQQuxTmTL8f3Y2kJEBeHpKG48limy2X2s4evQounfvjsDAQCgUCmzbti3f+xw5cgShoaFwd3dHlSpVsGTJEtsHagNnzgBr1ujWGzaULhZCCCH2SZOQALyWRE5snpC89dZbmDFjhsH2H374Ab1797boWGlpaWjYsCEWLFhg1v7R0dHo2rUr2rRpg6ioKEycOBGjR4/G5s2bLTqvPejQQbdctizg5iZdLIQQQuyTnBMSm19lc+TIEUyaNMlg+6uvvopZs2ZZdKwuXbqgS5cuZu+/ZMkSVKpUCXPmzAEA1K5dG2fPnsWsWbPQq1cvi84tpYwM8aR63t6ShUIIIcSOCb8f5Nax1eYJyfPnz+Hq6mqwXalUIkU47KgNnDx5EuHh4aJtnTt3xvLly6FSqYzOPJyVlYWsrCztuiZGlUoFlUpllbg0xzH3eJcuAYAu1pwcBpUqxyqx2IKl5ZMTRy4bQOWTM0cuG0DlM5eXlxMAZwDAw4c5UKlYYUMrFEvKY/OEpF69etiwYQO+/vpr0fb169ejTp06Nj13YmIi/Pz8RNv8/PyQk5ODR48eIcDIUKfTp0/HlClTDLbv27cPnlbuHRQZGWnWfocOVQQQql1PScnC7t17rRqLLZhbPjly5LIBVD45c+SyAVS+/MTHhwBoAAA4cuQinJxirRBVwaWnp5u9r80Tkq+++gq9evXC7du30eFFR4gDBw5g3bp12Lhxo61PD4XeNU+MMaPbNSZMmICIiAjtekpKCoKCghAeHg4vLy+rxKRSqRAZGYlOnToZraXRd/y4uKuPQuGGrl27WiUWW7C0fHLiyGUDqHxy5shlA6h85nr6VIGlS/lypUoN0bVrfStFWDCWtITYPCF5/fXXsW3bNkybNg2bNm2Ch4cHGjRogP3796Ndu3Y2Pbe/vz8SExNF25KSkuDi4gIfHx+j93Fzc4ObkR6jSqXS6m8Cc4957Zp4vVo1hSzekLZ4zOyFI5cNoPLJmSOXDaDy5ad8ed1yaqozlEpnK0RVcJaUxeYJCQB069YN3bp1K4pTibRo0QI7duwQbdu3bx+aNm0qqxf0lSu6ZTc34OefpYuFEEKI/aKrbMxw7tw5XLt2DQqFAnXq1EHjxo0tPsbz589x69Yt7Xp0dDQuXLiAsmXLolKlSpgwYQLi4uKw5sWAHcOHD8eCBQsQERGB//3vfzh58iSWL1+OdevWWa1ctqZS6Wb4rV8fOHJE/IIjhBBCNCghyUNSUhL69OmDw4cPw9vbG4wxPHv2DO3bt8f69etRXli/lI+zZ8+iffv22nVNX4+BAwdi1apVSEhIQExMjPb2kJAQ7N69G2PGjMHChQsRGBiIefPmyeqS34QEPvwvAFSrRskIIYQQ04SX/VJCouejjz5CSkoKrly5gtq1awMArl69ioEDB2L06NEW1Va8/PLL2k6pxqxatcpgW7t27XD+/HmL47YX8fG65QoVpIuDEEKI/RP+aKVxSPT89ddf2L9/vzYZAYA6depg4cKFBmOEEENxcbrlwEDp4iCEEGL/3NwADw8+oKbcakhsPnS8Wq022oFUqVRCrVbb+vSyJ0xIqIaEEEJIfjTNNpSQ6OnQoQM+/vhjxAvaHuLi4jBmzBh07NjR1qeXvZs3dcuUkBBCCMmPptmGEhI9CxYsQGpqKoKDg1G1alVUq1YNISEhSE1Nxfz58219elljDNizhy+7uABhYdLGQwghxP5pEpL0dCA7W9pYLGHzPiRBQUE4f/48IiMjcf36dTDGUKdOHbzyyiu2PrXsJScDd+7w5ZYtASsNFEsIIcSB6V/6qzeDit0qsnFIOnXqhE6dOhXV6RyCsLqtUiXp4iCEECIfwkt/W7YEbt+WLBSL2CQhmTdvntn7jh492hYhOIRnz3TLpUtLFwchhBD5ENaQ3LkDpKTIo4bdJgnJTz/9ZNZ+CoWCEpI8COckksOLiRBCiPT0B9B88kQe3yE2SUiio6Ntcdhih2pICCGEWEp//NDHj4HKlaWJxRI2v8pGIzs7Gzdu3EBOTk5RnVL2qIaEEEKIpfQv9338WJo4LGXzhCQ9PR1Dhw6Fp6cn6tatq51rZvTo0ZgxY4atTy9rVENCCCHEUu3aidcpIXlhwoQJ+Pfff3H48GG4u7trt7/yyivYsGGDrU8va1RDQgghxFI9ewIlSujWKSF5Ydu2bViwYAFat24NhUKh3V6nTh3clsu1SBKhGhJCCCGWcnIC1q7VrQ8fLh71217ZPCF5+PAhfH19DbanpaWJEhRiiGpICCGEFETZsuL1qVOlicMSNk9IwsLCsGvXLu26JglZtmwZWrRoYevTy9rDh7pl/cu4CCGEEFNq1xavJyZKE4clbD5S6/Tp0/Hqq6/i6tWryMnJwdy5c3HlyhWcPHkSR44csfXpZU1z9bSLCxAYKG0shBBC5KN8eeDUKaB5c77+/Lm08ZjDZjUkFy5cAAC0bNkSf//9N9LT01G1alXs27cPfn5+OHnyJEJDQ211etljTDePTeXKPCkhhBBCzNWsma5zqxwSEpt9zTVp0gSNGzfGsGHD0K9fP6xevdpWp3JIjx/r+pBUrSptLIQQQuSpZEkgLU0eCYnNakj+/vtvNGnSBOPHj0dAQAD69++PQ4cO2ep0DufuXd1ycLBUURBCCJGzkiX5/2KdkLRo0QLLli1DYmIiFi9ejNjYWLzyyiuoWrUqvvvuO9y/f99Wp3YIwg6t/v7SxUEIIUS+NAlJWpq0cZjD5lfZeHh4YODAgTh8+DBu3ryJvn374ueff0ZISAi6du1q69PL1qNHuuVy5aSLgxBCiHxpEpLMTMDeZ24psrlsAKBq1aoYP348vvjiC3h5eWHv3r1FeXpZoYSEEEJIYQlHbLX3WpIiS0iOHDmCgQMHwt/fH+PGjUPPnj3x999/F9XpZYcSEkIIIYWlqSEB7H9wNJsmJLGxsfjmm29QtWpVtG/fHrdv38b8+fMRHx+PZcuWobnmAmligBISQgghhSVsppk9W7o4zGGzy347deqEQ4cOoXz58hgwYACGDBmCmjVr2up0DkczKBpACQkhhJCCuXxZvL5lC598zx7ZLCHx8PDA5s2b8dprr8HZ2dlWp3FIDx8C+/bxZYUC8PGRNh5CCCHyFBKiG2QTAHr14gNv2iObJSTbt2+31aEd3v79uuW2bQFPT+liIYQQIl/TpvERW4VycwF7rCco0qtsiHmE/UcGDpQuDkIIIfL20ktAv37ibY8fSxNLfighsUPChIQGRSOEEFIYU6aI14XfMfaEEhI7RFfYEEIIsZZq1YD339et794tXSx5oYTEDlFCQgghxJpCQnTLY8cCKpV0sZhCCYkdooSEEEKINXl4iNcTE6WJIy+UkNih5GT+39VVPMoeIYQQUhD6P24TEqSJIy+UkNghzUTIvr58HBJCCCGkMN58U7x++TK//NeeUEJiZ5KTdTUk1atLGwshhBDH4OkJLF2qWx86FHBxsa/h5CkhsTM3buiWaaR9Qggh1uLnZ7jt00/tZ1wSSkjszM2bumVKSAghhFhLpUrGt+/aVbRxmEIJiZ2JidEtV6kiXRyEEEIcS8OGhqO2AuLvHSlRQmJnhD2fAwKki4MQQohjUSiA334z3B4fX/SxGEMJiZ2hhIQQQogtzZ8vXl+0CHj6VJJQRCghsTOahEShMN4BiRBCCCmM//0PmD5dvG3ZMmliEaKExM5oEpJy5QClUtpYCCGEOB43N2D8ePG2FSukiUWIEhI7olbrhvOl5hpCCCG21KGDbrlMGeni0KCExI48eKCb8CgoSNpYCCGEOLaNG3XLJ08CT55IFwtACYldEV56VbmydHEQQghxfGXLAq1a6dZDQoCMDOnioYTEjggTElMD2BBCCCHW4u+vW372DNi3T7pYZJeQLFq0CCEhIXB3d0doaCiOHTtmct/Dhw9DoVAY/F2/fr0IIzYfJSSEEEKKUtmy4vUePYDjxyUJRV4JyYYNG/DJJ5/giy++QFRUFNq0aYMuXbogJp9h5m7cuIGEhATtX3U7nbXu8mXdckiIdHEQQggpHox1ZpVqbhtZJSSzZ8/G0KFDMWzYMNSuXRtz5sxBUFAQFi9enOf9fH194e/vr/1zdnYuoogtc+QI/+/mBjRqJGkohBBCigH9GhIAqFCh6OMAABdpTmu57OxsnDt3DuP1Lp4ODw/HiRMn8rxv48aNkZmZiTp16uDLL79E+/btTe6blZWFrKws7XpKSgoAQKVSQaW5BKaQNMcRHi8xEYiO5gOPNGumhrNzLqx0uiJnrHyOwpHLBlD55MyRywZQ+WyldGkF9FMBPz+V1b5/LCmPbBKSR48eITc3F356w5f6+fkhUTN4h56AgAAsXboUoaGhyMrKwq+//oqOHTvi8OHDaNu2rdH7TJ8+HVOmTDHYvm/fPnh6eha+IAKRkZHa5UuXfAC0BgB4eUVj9+7LJu4lH8LyORpHLhtA5ZMzRy4bQOWztlu3KgBoKtp25sxuOFmp/SQ9Pd3sfWWTkGgoFArROmPMYJtGzZo1UbNmTe16ixYtEBsbi1mzZplMSCZMmICIiAjtekpKCoKCghAeHg4vLy8rlIBnjJGRkejUqROUL4ZjjY/XlaFz52B07SrfXq3GyucoHLlsAJVPzhy5bACVz1ZSUw2/P197ravVjq9pZTCHbBKScuXKwdnZ2aA2JCkpyaDWJC/NmzfH2rVrTd7u5uYGNzc3g+1KpdLqLxLhMW/d0m2vXdsZSqV99nOxhC0eM3vhyGUDqHxy5shlA6h81hYYaDwGa7HkWLLp1Orq6orQ0FCD6qzIyEi0bNnS7ONERUUhwA7HZY+O1i1XqyZdHIQQQoqP9u2Bzp1167NmSReLbGpIACAiIgL9+/dH06ZN0aJFCyxduhQxMTEYPnw4AN7cEhcXhzVr1gAA5syZg+DgYNStWxfZ2dlYu3YtNm/ejM2bN0tZDKM0k+oBNI8NIYSQoqFQAH/9BWRlAbGx0v4gllVC8s477yA5ORlTp05FQkIC6tWrh927d6Pyi3HWExISRGOSZGdnY+zYsYiLi4OHhwfq1q2LXbt2oWtX67WPWYtwll9XV2ljIYQQUry4uUlfOy+rhAQARowYgREjRhi9bdWqVaL1cePGYdy4cUUQVeEwppvlVziMLyGEEFJcyKYPiSN7+pRXlwHUXEMIIaR4ooTEDlD/EUIIIcUdJSR2QHglMzXZEEIIKY4oIbEDVENCCCGkuKOExA5QQkIIIaS4o4TEDlCTDSGEkOKOEhI7QDUkhBBCijtKSOxAfLxumRISQgghxRElJHbg+nX+38cHKFlS2lgIIYQQKVBCIrGHD3V9SBo04PMKEEIIIcUNJSQSu3BBt9yggWRhEEIIIZKihERif/yhW27WTLo4CCGEEClRQiKxyEj+39MTeP11aWMhhBBCpEIJicSSk/n/ypWBEiWkjYUQQgiRCiUkEsrJAZ4/58ve3pKGQgghhEiKEhIJpaTolkuXli4OQgghRGqUkEjo2TPdMtWQEEIIKc4oIZHQ06e6ZaohIYQQUpxRQiKhlBTdKGhUQ0IIIaQ4o4REQlRDQgghhHCUkEiI+pAQQgghHCUkEnr4kJpsCCGEEIASEkn9848uIalbV8JACCGEEIlRQiKhU6d4QuLlRQkJIYSQ4s1F6gCKq4wMFyQk8ISkUSPA2VnaeAghhBRMbm4uVCpVoY6hUqng4uKCzMxM5ObmWiky21MqlXC20hcYJSQSefzYTbtcoYKEgRBCCCkQxhgSExPxVHjJZCGO5e/vj9jYWCgUivzvYEe8vb3h7+9f6LgpIZHIkyfu2uWAAAkDIYQQUiCaZMTX1xeenp6F+kJWq9V4/vw5SpYsCScnefSmYIwhPT0dSUlJAICAQn6ZUUIiEUpICCFEvnJzc7XJiI+PT6GPp1arkZ2dDXd3d9kkJADg4eEBAEhKSoKvr2+hmm/kU2oH8+SJrsmGEhJCCJEXTZ8RT09PiSORnuYxKGw/GkpIJPL4sa6GJDBQwkAIIYQUmNz6e9iCtR4DSkgkQk02hBBCiA4lJBKhhIQQQgjRoYREIpo+JB4efGA0QgghpDijhEQimhqSgACAmiAJIYQUlQYNGmDSpElGb5s2bRrKlCmDhw8fFnFUdNmvJDIzgefPXQFQcw0hhJCi1aBBA1y6dMlge2JiIqZPn47vvvsO5cuXL/K4qIZEAvHxumW6woYQQkhRql+/Pi5fvmywfeLEiahcuTJGjBghQVRUQyKJu3d1bTTBwdLFQQghpPipX78+bt++jYyMDO3AZlFRUVi9ejUiIyPh4iJNakAJiQTu3tUth4RIFgYhhBAratoUSEws6L0VYMyrQGN6+PsDZ8+av3/9+vWhVqtx7do1NGnSBADwySef4M0330SHDh0AADt37sTevXsxf/58i+MpKEpIJBAdrXvBUUJCCCGOITERiIsr6L0VL/5sLygoCN7e3rh06RKaNGmCTZs24cyZM7h27Zp2n4sXL6Jx48ZFEo8GJSQSuHePEhJCCHE0/v6FuTcDY+xFDYlliUlBzqvpR5KVlYVx48Zh3LhxqFy5svb2ixcv4smTJwgNDUVmZia2bt2KGjVqWH4iC1BCIgHh1VR0lQ0hhDgGS5pN9KnVDCkpKfDy8oKTk+1rSjQJyezZs5Gbm4vPP/9cdPvFixfRqlUrnDt3DkuWLMHs2bOxZMkSm8ZEV9lI4NEj/mJTKhlKlZI4GEIIIcVO/fr1cfbsWUyfPh0//vijtnMrAGRlZSE7OxsjR44EwC8TfvTokc1jooREAsnJ/H+5cjQoGiGEkKJXv359PHr0CE2bNsVbb70luu3KlSuoU6cOnJx4ihAVFYUGDRrYPCZqspGAJtEsW1baOAghhBRPrVq1AmPM6G0XL17E7du3oVKp8OTJE6xatQp79uyxeUyUkBSx9HQgM5NXi5Qrx1BUvaoJIYQQc1y6dAm9evVCWFgY1Go1fvrpJ5QrV87m55Vdk82iRYsQEhICd3d3hIaG4tixY3nuf+TIEYSGhsLd3R1VqlSxeaec/Aib4Xx8pIuDEEIIMebHH3/E1KlTceHCBVy8eBEdO3YskvPKKiHZsGEDPvnkE3zxxReIiopCmzZt0KVLF8TExBjdPzo6Gl27dkWbNm0QFRWFiRMnYvTo0di8eXMRR64jTkiMV5cRQgghxY2sEpLZs2dj6NChGDZsGGrXro05c+YgKCgIixcvNrr/kiVLUKlSJcyZMwe1a9fGsGHDMGTIEMyaNauII9fRdGgFqIaEEEII0ZBNH5Ls7GycO3cO48ePF20PDw/HiRMnjN7n5MmTCA8PF23r3Lkzli9fDpVKBaVSaXCfrKwsZGVladdTUlIAACqVCiqVqrDFQK1awJo1avz993W8+mpNqFTqQh/T3mgeJ2s8XvbGkcsGUPnkzJHLBthf+VQqFRhjUKvVUKsL/zmu6WCqOaacqNVqMMagUqng7Owsus2S50s2CcmjR4+Qm5sLPz8/0XY/Pz8kmpg8IDEx0ej+OTk5ePToEQKMjEo2ffp0TJkyxWD7vn374OnpWYgS6Hh5AV26AE+f3sXu3VY5pF2KjIyUOgSbceSyAVQ+OXPksgH2Uz4XFxf4+/vj+fPnyM7OttpxU1NTrXasopKdnY2MjAwcPXoUOTk5otvS09PNPo5sEhIN/YmHdEPtmr+/se0aEyZMQEREhHY9JSUFQUFBCA8Ph5eXV0HDFlGpVIiMjESnTp2M1tLInSOXz5HLBlD55MyRywbYX/mysrIQExODEiVKiAYVKyjGGFJTU1GqVKkCTbAnJc2swe3atYObm5voNk0rgzlkk5CUK1cOzs7OBrUhSUlJBrUgGv7+/kb3d3FxgY+JDhxubm4GDygAKJVKq78JbHFMe+LI5XPksgFUPjlz5LIB9lM+JycnKBQKZGZmokSJEoU+nqaZRqFQaAckk4vMzEwoFAp4eHgYNNlY8lzJJiFxdXVFaGgoIiMj8eabb2q3R0ZG4o033jB6nxYtWmDHjh2ibfv27UPTpk3t4gVNCCFEnpydneHt7Y2kpCQAgKenZ6FqNtRqNbKzs5GZmSmbhIQxhvT0dCQlJcHb29sgGbGUbBISAIiIiED//v3RtGlTtGjRAkuXLkVMTAyGDx8OgDe3xMXFYc2aNQCA4cOHY8GCBYiIiMD//vc/nDx5EsuXL8e6deukLAYhhBAH4P9iml1NUlIYjDFt04fcmmy8vb21j0VhyCoheeedd5CcnIypU6ciISEB9erVw+7du7VTJickJIjGJAkJCcHu3bsxZswYLFy4EIGBgZg3bx569eolVREIIYQ4CIVCgYCAAPj6+hb66h+VSoWjR4+ibdu2sqrBVyqVha4Z0ZBVQgIAI0aMwIgRI4zetmrVKoNt7dq1w/nz520cFSGEkOLK2dm50F/Kzs7OyMnJgbu7u6wSEmuSR0MVIYQQQhwaJSSEEEIIkRwlJIQQQgiRnOz6kBQ1zUBqlgzukh+VSoX09HSkpKQ4ZFuhI5fPkcsGUPnkzJHLBlD55Erz3an5Ls0LJST50AzjGxQUJHEkhBBCiDylpqaidOnSee6jYOakLcWYWq1GfHy8VYfz1QxHHxsba7Xh6O2JI5fPkcsGUPnkzJHLBlD55EozJH5gYGC+A75RDUk+nJycULFiRZsc28vLy6FeePocuXyOXDaAyidnjlw2gMonR/nVjGhQp1ZCCCGESI4SEkIIIYRIjhISCbi5uWHSpElGZxV2BI5cPkcuG0DlkzNHLhtA5SsOqFMrIYQQQiRHNSSEEEIIkRwlJIQQQgiRHCUkhBBCCJEcJSSEEEIIkRwlJBJYtGgRQkJC4O7ujtDQUBw7dkzqkPJ19OhRdO/eHYGBgVAoFNi2bZvodsYYJk+ejMDAQHh4eODll1/GlStXRPtkZWXho48+Qrly5VCiRAm8/vrruH//fhGWwrjp06cjLCwMpUqVgq+vL3r06IEbN26I9pFz+RYvXowGDRpoB1xq0aIF9uzZo71dzmXTN336dCgUCnzyySfabXIu3+TJk6FQKER//v7+2tvlXDaNuLg4vPfee/Dx8YGnpycaNWqEc+fOaW+XaxmDg4MNnjuFQoGRI0cCkG+5bIqRIrV+/XqmVCrZsmXL2NWrV9nHH3/MSpQowe7duyd1aHnavXs3++KLL9jmzZsZALZ161bR7TNmzGClSpVimzdvZpcuXWLvvPMOCwgIYCkpKdp9hg8fzipUqMAiIyPZ+fPnWfv27VnDhg1ZTk5OEZdGrHPnzmzlypXs8uXL7MKFC6xbt26sUqVK7Pnz59p95Fy+7du3s127drEbN26wGzdusIkTJzKlUskuX77MGJN32YT++ecfFhwczBo0aMA+/vhj7XY5l2/SpEmsbt26LCEhQfuXlJSkvV3OZWOMscePH7PKlSuzQYMGsdOnT7Po6Gi2f/9+duvWLe0+ci1jUlKS6HmLjIxkANihQ4cYY/Itly1RQlLEXnrpJTZ8+HDRtlq1arHx48dLFJHl9BMStVrN/P392YwZM7TbMjMzWenSpdmSJUsYY4w9ffqUKZVKtn79eu0+cXFxzMnJif31119FFrs5kpKSGAB25MgRxpjjlY8xxsqUKcN++eUXhylbamoqq169OouMjGTt2rXTJiRyL9+kSZNYw4YNjd4m97Ixxtjnn3/OWrdubfJ2Ryijxscff8yqVq3K1Gq1Q5XLmqjJpghlZ2fj3LlzCA8PF20PDw/HiRMnJIqq8KKjo5GYmCgql5ubG9q1a6ct17lz56BSqUT7BAYGol69enZX9mfPngEAypYtC8Cxypebm4v169cjLS0NLVq0cJiyjRw5Et26dcMrr7wi2u4I5fvvv/8QGBiIkJAQ9OnTB3fu3AHgGGXbvn07mjZtit69e8PX1xeNGzfGsmXLtLc7QhkB/tm/du1aDBkyBAqFwmHKZW2UkBShR48eITc3F35+fqLtfn5+SExMlCiqwtPEnle5EhMT4erqijJlypjcxx4wxhAREYHWrVujXr16AByjfJcuXULJkiXh5uaG4cOHY+vWrahTp45DlG39+vU4f/48pk+fbnCb3MvXrFkzrFmzBnv37sWyZcuQmJiIli1bIjk5WfZlA4A7d+5g8eLFqF69Ovbu3Yvhw4dj9OjRWLNmDQD5P38a27Ztw9OnTzFo0CAAjlMua6PZfiWgUChE64wxg21yVJBy2VvZR40ahYsXL+L48eMGt8m5fDVr1sSFCxfw9OlTbN68GQMHDsSRI0e0t8u1bLGxsfj444+xb98+uLu7m9xPruXr0qWLdrl+/fpo0aIFqlatitWrV6N58+YA5Fs2AFCr1WjatCmmTZsGAGjcuDGuXLmCxYsXY8CAAdr95FxGAFi+fDm6dOmCwMBA0Xa5l8vaqIakCJUrVw7Ozs4G2W1SUpJBpiwnml7/eZXL398f2dnZePLkicl9pPbRRx9h+/btOHToECpWrKjd7gjlc3V1RbVq1dC0aVNMnz4dDRs2xNy5c2VftnPnziEpKQmhoaFwcXGBi4sLjhw5gnnz5sHFxUUbn1zLp69EiRKoX78+/vvvP9k/dwAQEBCAOnXqiLbVrl0bMTExABzjvXfv3j3s378fw4YN025zhHLZAiUkRcjV1RWhoaGIjIwUbY+MjETLli0liqrwQkJC4O/vLypXdnY2jhw5oi1XaGgolEqlaJ+EhARcvnxZ8rIzxjBq1Chs2bIFBw8eREhIiOh2uZfPGMYYsrKyZF+2jh074tKlS7hw4YL2r2nTpnj33Xdx4cIFVKlSRdbl05eVlYVr164hICBA9s8dALRq1crgEvubN2+icuXKABzjvbdy5Ur4+vqiW7du2m2OUC6bKOpetMWd5rLf5cuXs6tXr7JPPvmElShRgt29e1fq0PKUmprKoqKiWFRUFAPAZs+ezaKiorSXK8+YMYOVLl2abdmyhV26dIn17dvX6CVsFStWZPv372fnz59nHTp0sItL2D788ENWunRpdvjwYdFleunp6dp95Fy+CRMmsKNHj7Lo6Gh28eJFNnHiRObk5MT27dvHGJN32YwRXmXDmLzL9+mnn7LDhw+zO3fusFOnTrHXXnuNlSpVSvt5IeeyMcYv1XZxcWHfffcd+++//9hvv/3GPD092dq1a7X7yLmMubm5rFKlSuzzzz83uE3O5bIVSkgksHDhQla5cmXm6urKmjRpor281J4dOnSIATD4GzhwIGOMX543adIk5u/vz9zc3Fjbtm3ZpUuXRMfIyMhgo0aNYmXLlmUeHh7stddeYzExMRKURsxYuQCwlStXaveRc/mGDBmifb2VL1+edezYUZuMMCbvshmjn5DIuXyasSmUSiULDAxkPXv2ZFeuXNHeLueyaezYsYPVq1ePubm5sVq1arGlS5eKbpdzGffu3csAsBs3bhjcJudy2YqCMcYkqZohhBBCCHmB+pAQQgghRHKUkBBCCCFEcpSQEEIIIURylJAQQgghRHKUkBBCCCFEcpSQEEIIIURylJAQQgghRHKUkBBCCCFEcpSQEEIIIURylJAQQgghRHKUkBBCCCFEcpSQEEIIIURylJAQQgghRHKUkBBCCCFEcpSQEGIjU6dORZ06daBWq7XbUlNTMW7cOISHh6N8+fJQKBSYPHmywX2XL1+OChUqIC0tzWrxzJs3DwqFAvXq1bPaMa1p1apVUCgUuHv3rtShWMzWsesf/8SJE5g8eTKePn1qk/MRIgVKSAixgfj4eMycORNTp06Fk5PubZacnIylS5ciKysLPXr0MHn/gQMHokSJEpg5c6bVYlqxYgUA4MqVKzh9+rTVjktsr1u3bjh58iQCAgIA8IRkypQplJAQh0IJCSE2MHfuXHh7e6Nnz56i7ZUrV8aTJ09w5MgRTJ8+3eT9XVxc8MEHH2Du3LlIT08vdDxnz57Fv//+i27dugHgNTCOzhqPm70oX748mjdvDjc3N6lDIcRmKCEhxEyDBg1CcHCwwfbJkydDoVBo17Ozs7F8+XL069dPVDsCAAqFQrRvXt59912kpKRg/fr1hYob0CUgM2bMQMuWLbF+/XqDL2xNOa5cuYK+ffuidOnS8PPzw5AhQ/Ds2TODY/75559o0KAB3NzcUKVKFcydO9fgsTD3MTPm1q1bGDx4MKpXrw5PT09UqFAB3bt3x6VLl0we7/z583jrrbdQpkwZVK1a1ehxt23bBoVCgQMHDhjctnjxYigUCly8eFG77b///kO/fv3g6+sLNzc31K5dGwsXLswzdgA4fvw4OnbsiFKlSsHT0xMtW7bErl27jO57/fp19O3bF35+fnBzc0OlSpUwYMAAZGVlARA32UyePBmfffYZACAkJET7mjp8+DCOHTsGhUKBdevWGZxjzZo1UCgUOHPmTJ5xx8bGwsvLCx999JHR2589ewaFQoEPP/ww38eAEEtQQkKIlZ0+fRrJyclo3759oY7j7++PWrVqGf0SUygUePnll806TkZGBtatW4ewsDDUq1cPQ4YMQWpqKjZu3Gh0/169eqFGjRrYvHkzxo8fj99//x1jxowR7fPXX3+hZ8+e8PHxwYYNGzBz5kysW7cOq1evtricpsTHx8PHxwczZszAX3/9hYULF8LFxQXNmjXDjRs3jN6nZ8+eqFatGjZu3IglS5YY3ee1116Dr68vVq5caXDbqlWr0KRJEzRo0AAAcPXqVYSFheHy5cv48ccfsXPnTnTr1g2jR4/GlClTTMZ+5MgRdOjQAc+ePcPy5cuxbt06lCpVCt27d8eGDRtE+/77778ICwvDqVOnMHXqVOzZswfTp09HVlYWsrOzDY49bNgwbbKwZcsWnDx5EidPnkSTJk3Qpk0bNG7c2GjCtGDBAoSFhSEsLMxk3AAwevRouLq64rvvvjN6e+nSpREYGIhTp07leRxCLMYIIWYZOHAgq1y5ssH2SZMmMeFb6fvvv2cAWGJiYp7He/jwIQPAJk2aZHKfd999l/n5+Rlsd3Z2Zh06dDAr7jVr1jAAbMmSJYwxxlJTU1nJkiVZmzZtjJZj5syZou0jRoxg7u7uTK1Wa7eFhYWxoKAglpWVpd2WmprKfHx8RI+FuY8ZY4ytXLmSAWDR0dFGy5GTk8Oys7NZ9erV2ZgxY4we7+uvvzb9QAhEREQwDw8P9vTpU+22q1evMgBs/vz52m2dO3dmFStWZM+ePRPdf9SoUczd3Z09fvzYaOzNmzdnvr6+LDU1VRR/vXr1WMWKFUWPZYcOHZi3tzdLSkoyGa/+8X/44QeTj5Vm36ioKO22f/75hwFgq1evzvNxOX36NAPApk2blud+LVu2ZGXKlNGuq9VqVqpUqTzLQEh+qIaEECuLj4+HQqFAuXLlCn0sX19fJCUlIScnR7Q9JyfHaJODMcuXL4eHhwf69OkDAChZsiR69+6NY8eO4b///jPY//XXXxetN2jQAJmZmUhKSgIApKWl4ezZs+jRowdcXV21+5UsWRLdu3e3qHx5ycnJwbRp01CnTh24urrCxcUFrq6u+O+//3Dt2jWj9+nVq5dZxx4yZAgyMjJEtRUrV66Em5sb+vXrBwDIzMzEgQMH8Oabb8LT0xM5OTnav65duyIzM9NoLUFaWhpOnz6Nt956CyVLltRud3Z2Rv/+/XH//n1tDU96ejqOHDmCt99+G+XLlzf7sclL37594evrK6olmT9/PsqXL4933nknz/suXrwYTk5OGDJkiHbbwYMHDZqA0tLSwBjTrt+6dQs+Pj5WKwMpnighIcTKMjIyoFQq4ezsXOhjubu7gzGGzMzMAt3/1q1bOHr0KLp16wbGGJ4+fYqnT5/irbfeAqC78kbIx8dHtK7pSJmRkQEAePLkCRhj8PPzM7ivsW0FFRERga+++go9evTAjh07cPr0aZw5cwYNGzbUxqJPcxVKfurWrYuwsDBts01ubi7Wrl2LN954A2XLlgXAr4jKycnB/PnzoVQqRX9du3YFADx69Mjg2JrHx1gsgYGB2mNr9s3NzUXFihXNitscbm5u+OCDD/D777/j6dOnePjwIf744w8MGzYs306xkZGRqFu3ruh5nDx5MjZt2iTa78GDB6hWrZp2PSoqCg0bNsSQIUPg5eWFl156CdHR0VYrEykeKCEhxEzu7u7aToZC+l9K5cqVQ3Z2tlXGEHn8+DHc3NxEv7QtsWLFCjDGsGnTJpQpU0b7p7naZvXq1cjNzbXomGXKlIFCocCDBw8MbktMTBStm/uYGbN27VoMGDAA06ZNQ+fOnfHSSy+hadOmed7X3A7DADB48GCcOnUK165dw19//YWEhAQMHjxYe3uZMmXg7OyMQYMG4cyZM0b/NImJUJkyZeDk5ISEhASD2+Lj4wFAW3tWtmxZODs74/79+2bHbY4PP/wQKpUKK1aswLJly5CTk4Phw4fneZ+MjAzExcWJOgM/fvwYp06dQqVKlbTbLl++jMTERFEfqaioKJw8eRL9+/fHo0ePUKNGDXz11VdWLRNxfJSQEGKm4OBgJCUlib6Is7OzsXfvXtF+tWrVAgDcvn270Oe8c+cO6tSpU6D75ubmYvXq1ahatSoOHTpk8Pfpp58iISEBe/bssei4JUqUQNOmTbFt2zZRp8vnz59j586don3NfcyMUSgUBr/od+3ahbi4OIviNaVv375wd3fHqlWrsGrVKlSoUAHh4eHa2z09PdG+fXtERUWhQYMGaNq0qcGffm0SwB+fZs2aYcuWLaKaHLVajbVr16JixYqoUaMGAMDDwwPt2rXDxo0bzUrSNPRrrfQFBASgd+/eWLRoEZYsWYLu3buLkgpjNImpsDZuyZIlcHZ2Fj3Pc+fOhZOTkyh5i4qKwsSJE9G+fXu4urpiwIABuHLlitnlIQQAdWolxFx37txhSqWSvfzyy2zXrl1s8+bNrF27diwkJETUQTMmJoYBYD///LPR4+zevZtt3LiRrVixggFgvXv3Zhs3bmQbN25kaWlp2v1yc3NZ6dKlWUREhMExzOnUumPHDgaAff/990Zvf/jwIXNzc2M9evRgjOk6hj58+FC0n7HOpnv27GFOTk7s5ZdfZlu3bmWbNm1izZo1Y5UrV2YKhcLix8zYeQYMGMDc3NzYTz/9xA4cOMBmzpzJypcvzypWrMjatWsnuq+p2PPTt29f5uvry1xdXdnEiRMNbr9y5QorU6YMe+mll9jKlSvZoUOH2Pbt29ns2bNZ+/btTcZ++PBhplQqWbNmzdjGjRvZn3/+yTp37swUCgVbv3696BwXLlxgJUuWZFWqVGFLly5lBw8eZOvWrWN9+/ZlKSkpRo9/6NAhBoB98MEH7MSJE+zMmTPafTU0HVQBsP3795v1eNSoUYO5urqy5cuXs8WLF7MyZcqwsWPHssDAQLZjxw722WefMQAGr0lfX19279497fratWtZx44dzTonIRqUkBBigd27d7NGjRoxDw8PVqVKFbZgwQKjV4y0adOGde3a1egxKleurP2i0P8TfukfOHCAAWDnzp0zOAYAgy9lfT169GCurq55XvnQp08f5uLiwhITEy1KSBhjbOvWrax+/frM1dWVVapUic2YMYONHj1adPUFY+Y/ZvrnefLkCRs6dCjz9fVlnp6erHXr1uzYsWOsXbt2VktI9u3bp33sb968aXSf6OhoNmTIEFahQgWmVCpZ+fLlWcuWLdm3336b52N07Ngx1qFDB1aiRAnm4eHBmjdvznbs2GH0HFevXmW9e/dmPj4+2sdz0KBBLDMz0+TxJ0yYwAIDA5mTkxMDwA4dOmRw3ODgYFa7dm2zH49Tp06x+vXrMzc3N1avXj0WGRnJkpOTWdu2bZmbmxsLCQlhM2fOFF0lFBcXxwCw9PR07ba33nqLzZo1y+zzEsIYYwrGBF2lCSFWsXnzZrzzzju4d+8eKlSoUKBj9O/fH3fu3MHff/9t5ehsQ6VSoVGjRqhQoQL27dsndTjF3sWLF9GwYUMsXLgQI0aMsNl5du3ahR49euCXX37Bu+++izVr1mDatGmIiopCqVKlbHZe4ngoISHEBhhjaNmyJUJDQ7FgwQKL73/79m3Url0bBw8eROvWrW0QYeENHToUnTp1QkBAABITE7FkyRIcOXIE+/btwyuvvCJ1eMXW7du3ce/ePUycOBExMTG4desWPD09bXa+b7/9FgkJCYiOjsaJEycQGhqKZcuWoUqVKjY7J3FMLlIHQIgjUigUWLZsGbZv3w61Wm0whHx+YmJisGDBArtNRgA+c/HYsWPx8OFDKJVKNGnSBLt376ZkRGLffPMNfv31V9SuXRsbN260aTICAF9++aVNj0+KD6ohIYQQQojk6LJfQgghhEiOEhJCCCGESI4SEkIIIYRIjjq15kOtViM+Ph6lSpWyaFhqQgghpLhjjCE1NRWBgYH5du6nhCQf8fHxCAoKkjoMQgghRLZiY2PznUSSEpJ8aAb2iY2NhZeXl1WOqVKpsG/fPoSHh0OpVFrlmPbEkcvnyGUDqHxy5shlA6h8cpWSkoKgoCCzBsmjhCQfmmYaLy8vqyYknp6e8PLycqgXnoYjl8+RywZQ+eTMkcsGUPnkzpwuD9SplRBCCCGSo4SEEEIIIZKjhIQQQgghkqM+JIQQQoiFGGPIyclBbm6uVY6nUqng4uKCzMxMqx2zKDg7O8PFxcUqw2JQQkIIIYRYIDs7GwkJCUhPT7faMRlj8Pf3R2xsrOzGvPL09ERAQABcXV0LdRxKSAghhBAzqdVqREdHw9nZGYGBgXB1dbVKAqFWq/H8+XOULFnS4tnBpcIYQ3Z2Nh4+fIjo6GhUr169ULFTQkIIIYSYKTs7G2q1GkFBQfD09LTacdVqNbKzs+Hu7i6bhAQAPDw8oFQqce/ePW38BSWfUhNCCCF2Qk5Jg61Z67GgR5QYyskBtm8HrlyROhJiDz75BKhfHzhzRupICCEOjBISYuiXX4A33gCaNgUeP5Y6GiKVmBigRw9g7lzg8mVgwACpIyKEODBKSIihDz/k/zMzgc2bpY2FSKdvX+DPP3Xr169LFwshxOFRQkLy5uEhdQREKidOSB0BIaQYoYSE5M2KvciJzLnQRXmEyN2oUaPQunVro7cFBwfju+++K+KIdOgThuSNEhKi4e8vdQSEkEK4evUqFi9ejKNHjxq9vXbt2rhw4ULRBiVACQnJG13aRjTu3weOHQPatJE6EkLsS9OmQGJioQ6hAODFmGWDrPn7A2fPmr37Dz/8gLCwMLRq1cro7WXLlkVsbCwAYOfOndi7dy/mz59vfjyFRAkJyZuM5lQgRaBtW4AxqaMgxL4kJgJxcYU6hOLFn63k5ORg8+bN+Oqrr7TbPvjgA7z00ksYOnQoACA1NRUlSpQAAFy8eBGNGze2YUSGKCEhecvJkToCQgixb1ZozmTgQ7ErFArzExMLznv79m2kpqaifv36APjIsBs3bkSHDh20+1y8eBE9e/bULj958gShoaHIzMzE1q1bUaNGDbPPVxCUkJC8UQ0JIYTkzYJmE1OYWo2UlBR4eXlBYYOm8qdPnwIASpYsCQDYu3cvnjx5op0Q759//sG9e/fQo0cPADwhadWqFc6dO4clS5Zg9uzZWLJkidXjEqKEhIhlZYnXqYakeFKrpY6AEGJFlStXhkKhwLp161CiRAl8+umn6Nq1K/78808EBwfjgw8+QIcOHdC2bVtkZWUhOzsbI0eOBAA0aNAA+/fvt3mM1GORiKWkiNephqR4UqmkjoAQYkX+/v747rvvsHbtWnTp0gURERGYPn06jhw5gtatW6NmzZrYuHEjAODKlSuoU6eOdo6aqKgoNGjQwOYxUg0JEUtLE69TDUnxpF9TRgiRvQkTJmDChAmibdHR0Qb7Xbx4Ebdv34ZKpcKTJ0+watUq7Nmzx+bxUUJCxPQTEKohKZ4oISGk2Lp06RJ69eqFsLAwqNVq/PTTTyhXrpzNz0sJCRHTT0CohqR4ooSEkGLrxx9/BABMnTq1SM9LfUiIGCUkBACys3XLXbvqlsuUKfpYCCHFAiUkREw/IaEmm+JJWEPi6wvUqcOXqbMrIcRGKCEhYlRDQgBxQuLmBiiVfJkSEkKIjVBCQsSohoQAUAgTD1dXSkgIITZHCQkR068RoRqS4slUDYlaTUkqIeDDvBPOWo+F7BKSRYsWISQkBO7u7ggNDcWxY8dM7rtlyxZ06tQJ5cuXh5eXF1q0aIG9e/cWYbQyRDUkBDBMSF4MLw2AaklIsaZ8kZynp6dLHIn90DwWmsemoGR12e+GDRvwySefYNGiRWjVqhV+/vlndOnSBVevXkWlSpUM9j969Cg6deqEadOmwdvbGytXrkT37t1x+vTpIp/FUDaoDwkBxAmJsMkG4AmJu3vRx0SIHXB2doa3tzeSkpIAAJ6enlAoCj9Pr1qtRnZ2NjIzM7UjpNo7xhjS09ORlJQEb29vODs7F+p4skpIZs+ejaFDh2LYsGEAgDlz5mDv3r1YvHgxpk+fbrD/nDlzROvTpk3Dn3/+iR07dlBCYgrVkBBAfNmvsMkGoBoSUuz5v5hlV5OUWANjDBkZGfDw8LBKglOUvL29tY9JYcgmIcnOzsa5c+cwfvx40fbw8HCcOHHCrGOo1WqkpqaibNmyJvfJyspCluDXYcqLuV1UKhVUVvog1hzHWsezJkVWluhFkZuVBbWFcdpz+QrLkcsG6MqVm56ufR3kurhA4eysbd9VpacDpUpJEl9hOfLz58hlA+yvfOXKlUOZMmWQk5NjlT4UOTk5OHHiBFq2bAkXF3l8NSsUCri4uMDZ2Rk5JmrTLXm+5FFqAI8ePUJubi78/PxE2/38/JCYmGjWMX788UekpaXh7bffNrnP9OnTMWXKFIPt+/btg6enp2VB5yMyMtKqx7OG8lFRaClYv33zJq7t3l2gY9lj+azFkcsGALcPHMCLkUdwITYWAcnJCHyxfnDvXmQWwTDStuTIz58jlw1w/PIdPXpU6hCsypK+NrJJSDT0q7IYY2ZVb61btw6TJ0/Gn3/+CV9fX5P7TZgwAREREdr1lJQUBAUFITw8HF5eXgUPXEClUiEyMhKdOnUqdCcga1PotV1WrVwZIcKROs1gz+UrLEcuG6ArX81797TbGgwaBOfERODkSQBAh9atgSpVpAqxUBz5+XPksgFUPrlK0Z9BPg+ySUjKlSsHZ2dng9qQpKQkg1oTfRs2bMDQoUOxceNGvPLKK3nu6+bmBjc3N4PtSqXS6i8SWxyz0PSSO2cAzgWM0S7LZyWOXDafy5fhrPmV5ukJZf36vB/JC8r794GaNSWKzjoc+flz5LIBVD65saQs8ujKC8DV1RWhoaEG1XWRkZFo2bKliXvxmpFBgwbh999/R7du3WwdpvzRVTbFnv8//+hWWrYEnJ3FnVp79Sr6oAghDk82NSQAEBERgf79+6Np06Zo0aIFli5dipiYGAwfPhwAb26Ji4vDmjVrAPBkZMCAAZg7dy6aN2+urV3x8PBA6dKlJSuHXaOrbIq9Uvfv61Z++YX/FyYkz54VbUCEkGJBVgnJO++8g+TkZEydOhUJCQmoV68edu/ejcqVKwMAEhISEBMTo93/559/Rk5ODkaOHImRI0dqtw8cOBCrVq0q6vDlgWpIir1SmveQtzegGd+HXgeEEBuTVUICACNGjMCIESOM3qafZBw+fNj2ATkaqiEp3jIz4fnoEV+uVUvXp0i/ViQ3lzflEEIcw/Pn/H3t5WXQl7CoyKYPCSkiVENSvD19qlsWXo2mn5A8f14k4RBCisiqVbxWtEQJYNMmSUKghISImaohyc4Gfv0VMHMQOiJTwoTE21u3TAkJIY4tIYH/z8jgtSQSkF2TDbExUzUkc+cC48bx5dhYoGLFoo2LFAmFMPEQJiTCRAUAUlOLIhxCSFHRJCQAEBAgSQhUQ0LETNWQaJIRQLLqPGJ7ijNndCvChER/rB+qISHEsVBCQuyOOX1IZDLPghZjwIQJQPfuwLFjUkdjv1JS4CwYpViUkCxYIN6XEhJCHEt8PP+vVAI+PpKEQAkJETPnKhu5XV0xbhwwYwawcyfQqRM1N5iin6wJE5L69YGxY3Xr9BjKR1YW8PvvwL//Sh2JfN25A3z7LXD9utSR2I6mhsTfn66yIXZCPwFJSTH88pFTQvL338CsWbr1rCwgOpqXUzOrc3Iy8OabwNtvA0+eSBOnNWRk8L+Cio0VrwsTEkDcb4hqSORjzhzg3XeBNm34a72wHj7k7yu1uvDHkoMHD4BmzYCvvgLeeUfqaGxDpQI0l/sHBua9rw1RQkLE9BOSgwd5xiwkp4Rk2zbDbdevA1WrAu7ufOCvbt34fhs3AmXLAhcvFnWUhRcdzdt9g4KAuLiCHePaNfG6/pTqJUvqlqmGRD7Gj+f/U1OBP/4o3LGys4FGjYDWrYH58wsdml1jDDh7lo9WrPmyvnhRt+xIbt/Wvd81gyFKgBISImasiUZ/+mi59CFhDNiwwXD7l18CmtlsY2OB06fFty9fbvvYrCEjQ5cYfPIJvzQ3ORmYNs38YyQn657zW7fEt+nP6FuqlG6ZakjkKTq6cPc/eVLX1+CTTwodjl1btAgIC+OfF0Lnz0sTjy1duqRbrl9fsjAoISFi5ozMKpcakl69DJshAOC///K+nzWqtW3t8WMgJAQoVw6IihInVZpkKz+7d/Nalfr1gcxM3RcNgNwJE/gvYSGqIZEnYdPbnTuFO5a1m2mePuX9u/bvt+5xhRjjNb23b1t2v1GjjG+/cKHQIdmdy5d1y/XqSRYGJSSE01TXOUpCkpEBbN1asPt6ehb+/IwZNnlY0+rVvG07O5snXikputtKlACSkvhVRSNGmI7jgw942/G1a8BvvwEvJp/M8PGBesoUw/2phkSeXsz1BQAQTpyYl6ws4LXXgDp1xAl8drbp+xTk9T5zJr8CrlMn8WWnhfX0qa6P2MqVQMeOQIMG5pc/L/o1iY7g7l3dcs2akoVBCQkBYmL4vCXlygETJ+a/v0Q9sC3y4stVy5JqSOGXe0E8fcrPV7s2TxoK6skTPjKusV+lwi+G6GhxZ9YnT4CPPuJXFS1ebDoxE344nzrFkxgAmWXKGN9fWENCCYntqdW8Q+qyZZZ/2T96xL+QlywRX10TE8Nf38eO8S9Wlcr4/X/5Bdi1iyerNWoAV6/y7cZmemYM6NuXTzWgX9PBGLBlC7Bnj/HzTJ+uW96xw/zyJSWZruk8fx6oUIH3hYiP5+8FgDc9BwXx2sXCKGwtkz0SPq+m3v9FgBISArz/PnDzpvlNFXKYcE8/IalQwfz7FjYh+eor4MoV4MYNnuDdusXboYV9V4SiooAWLYDJk3XbVCqgSROgVSvgu+8M75NXLVV8vLjz4j//GN8vJES3fPSoNvExKyGhJhvbmzwZGDOGvz9PnuSvnbxqKF5QHD/Or5Rwdwc+/FB8Y0ICrzFp2xaoXp0nzsbGGtq4Ubw+aRL/rz9iL8BfX+vX8ySoUyfe92LvXp7QbNnCa/C6duUdRPOi+aJfsAAYPJi/j+rU4ccQSk7mndJr1AD27TM8zrx5PPlISuKPn6amRMOSxMcYS5t+5ECYkJQuLVkYMumdSGzK1BeWKfY44d7Nm7yGp2xZvq6fkJQsyX8dGetTAvBmGk3nXWO/Ai0hHO3033+Bzp11H7Y7d/IERFjL1L49P+epU8D//seTp5s3ddWoX3/NxwDx8NDdx9gXg4b+VTZHjgBr1wJ9+og7JFesqOvkePOmdnOWqYSEmmyKzsGDwDff6NbffZe/HgIDgQMHeI2mCc4jR5qu+QDEr50bN4Bz5/hrYepUnjz36yeuwgd0ozPrvzdUKt7sIjRypPHzhoXx+wvnSXFy0tUAXrnCa2I0NRoavXqJaoic1q/Xvf66dtV9Hh0+zGv9YmLEcVetKq5NKWwfsZgYXm6lsnDHsSea59XFRfw5U8SohoTwDwVLDBpk+KtDCpqams2bebtn3bq6S/L0E5Lhw4GXXjJ9LD8/3RuxsDUkwuaTc+fEVbz//ms4QJXwQ/7xY96m3rWreJ+//xYfN6+ERP+2U6eA/v354Fim4hRIMzVsNNWQFB396Rk0CUJ8PK8xMebxY7g9ecKTDEusXMkTkqVLeSI0bJjpjtH6Ccm2bYY1GHkZOlS87uqqW75/n79fjBk9Gk5LlsApK0ucVGs+A/7+m/cT6d8fOHRId7tabdi0U9ixhtRqPhaLI9F85nl5SdokTwkJKdgLcPZs68dhLpWK1ySULAl8/z3/ZQfwJKR8eT4AlPBX22uvAR06AA0bio8j/CXQvr2uqjIlhV91Ykm7fWYm76sRG5v/4GRHj+rKMWSI+LYVK/hVB8JfeQD/oPXy4skgkHdCYop+QmKkloMplYh9+WXj9/f01L1WHLHa2p7oJ9RCx4/z5ogLF3iS3awZ0LMnlP7+CB82DApLr4T5+ef891EoeHORfqLy9tuWnWvTJl2/qrQ0/r7RuHCB910xZv58OI8ejao7dhi+LxnjCby55X7RVypP+R2rMH3D7JEm0ZSwuQagJhv7EhPDq/O7dBH/crC1giQkwmaJovbVV7oPLs2gT0LHj4vXp07lZRT2mQB4W3d6Ov/1OWYMv19iIn8eypYFgoP5LzZzqjAnTeJJUKVK+bfzaz4Qt2/nv06F5swxfh/NF9Tq1bwKuiAJSYkS4vW0NINdWP36pptsnJx0Xwb37vEOjK+8YnkcJH95feExxjs7Dx5s8DpwslX/Lsb463Xt2sIfa8sW3rfFWGKgSdZN8Lp71/AqkPPnLavVNCch0U/Wy5XjydeiRXw9r4RRjjSPHyUkBAD/EgsL42+WyZN1nciKgqVNNoA0w0Y/fsyrqzdvtux+mpFmg4PF2xs2BBo31q0LL/fNyOBXGCxZwpOVPXuAvXuhCAtD00WLoFCp+GiVmmNramT0azaMefiQt5cXdBjqr78u2P30ry4w1g/Ezc38440d65hjMtiD/L7w3nyzaOIQ6t3bOsfRjIRcgBFPXVNTDZuNPvvMsoOYk5AIE5ymTXnyLUzGHKmGJDNT9yNK2L9HAtRkYy8uXtS9UYRXWxSFgtSQSJGQjB9veTIC8GYcwDAhqVtXvG5shstr1/gXb9euwNy5cHnvPVQ4cQIuvXvzQcWMjQSbn6VL+eBD1vg16+Sk+xApVy7vffW/5IzVkLRta/65C3v5JDHu6FHbXlrq7Ax88YV4m7HXfqVKwNy51j+/5su+AH05fP/9F87CuakAcZ8Rc5w4wd+DeXXOFyYk9evzmgPhFBqOVENiJ1fYABYmJDdu3MDkyZPRsWNHVK1aFQEBAWjQoAEGDhyI33//HVn20NFRrqScqKogNSS2HPTL2LmWL+fjMRSEphOcsLOmv79hs5ixtvRly4AffzR97D59LO9EaE2tWgGRkcAPP+Q/5L3wQ1Sl0v0q8vEBqlUD6tWDevRo88+tP5IrsQ5jl3lby5EjfJhwTV8kDWFNIcAv+71zh/e/Mka/+c+YsmX5Zbu//85n3NbQfNkXpNmxoJYt45cJa3zwgWFSJiR8r2iaMP38dNscqYZEmHzJISGJiopCp06d0LBhQxw9ehRhYWH45JNP8M033+C9994DYwxffPEFAgMD8f3331NiUhByS0iKMt4dO3jP/8JyduZXBbz9Nh8jQV/Vqrxzq6XyuATT5hYs4B0bx47Nf/C3p091nQiFtSNNm/IrES5d0tUmmSJ8HiT+8HJYxsbW0DDWZ8pctWvz8Udq1zZ8nhs21NX2BQXxCSednQ37XQF8ALS8Xmvh4bwMycm8abJvX13Hc0B3hVZRJiR16/K4hWbONH61GGM8cdPQJDLCvlWFHRrAngjLIocmmx49euCNN95AfHw8Dh48iBkzZuCjjz7CsGHDMG7cOKxZswbR0dHYuXMnzp07hx/z+kVJjJMyIbHnJpvbt4E33jB+myXNCxpvvME/eJs0MX57gwaWH9PasrJ4E97WrUC7dqb3+/prcbzmTBuuaWYR9h8RXs6bH+FEY2YM0kXMpFbzjtqbNhlvPgH44GPTp+tGAq5Ykddi/PBD/sf39RXXoJUuLf7yadSIJ+q3b/NmSk1HbmOfDZs25d3c2KEDHyBNyM1NN26HsSab2rVNH++99/iVRIVRpoxhQgIYznAN8HFUhAmUphOto47DY0dNNmZ1av3vv//gasZVHy1atECLFi2QTR9UlqMaEuPWrze+vU8f/uU4Zw4fZ0M4OVTZsrxMjx7xK3IsoX9psDV8+SW/QkHTmS8/rq78C6d+fZ6cCH+tCenPN2OsQ2rlyrx6WVMz8uQJT1yENSTmVL8bOwfVhFrPihX8UnahVq34+BoamknPSpfmY9kwxl/nbdrkfey1a3kthf77fP9+PnaHry/w+ut8m/4MzwDvbK+5qu677/j5hJfr6uvQwfh2Ly9ea/LsGb/SZulScdmEyUFAAPDrr7yZpF49XXzmatmS9xXRKFPGeO3fzZv8cXn+nCf/iYmGTbeaGlBHnTpBbk02+SUjT/Wq3sxJXogeqiExTn/CrerVebPBrFm8GnbZMt7UsH07v93JiTfHHDvGkxlz5uYRErYza7i6FqwpR+Obb/gXSEGuqunVi/dhWbKEJwAVK/Lt+lOiG3P3Lv8bMUK3TfOrVDMqLWDZZILC9zb98LAe/WQE4J1KhapX1y0rFLoE46WXeB8gfV99xZNWY8kIwBON5GTg+vW8q+p/+YW/RgIC+ACDgGFC0rMnf53Nn8+Pa4zmHHfu8Ne1sOOu5rgazs48WdIkYfk1JSoU/DJogNca9uwpvt1UDcmff/LHr317PgLuhg3iz7bWrXV9R4QJyZ49jnOFmdyabIS+//57bBBcWfD222/Dx8cHFSpUwL/6I1AS80k5HLs9JyTCERHv3OG/aJYtM5yb5rXXgN27+RUKzZvzXzXvvMPn87BE06a6L303Nz4vRmamwWXYuV9/zTvsaWiGrBdq2FB8VZCpEVCFhB3nAN4hNyKCd8JzdeVzmmzfbjoh0YziWaGC7jEStn1rEhLh4G2WPEZUQ1J0NH05gLzHJlIogN27kSv8Up87lzc7fP113jWgSqV45FNjGjTgVwDevat7nQsTknr1eDPOwoXAqFGmj2Pkqi6tkBBx06x+345+/QzvU7o0/9z89Vfgr794LdP16/w9ov/F6upqPKnZtEnXQb9TJ36Jv8akSbwvjObzUf/xb9KkaDv324odNdlYnJD8/PPPCAoKAgBERkYiMjISe/bsQZcuXfCZpdeDE5285p6wNXttsjl/XjxJnLFfOBoKBf/QbtWqcOd0c+NJzcaNvK3+o4/4sYW/TgGov/xSnMjpJxuffcZ/QQl/qZka42PrVv5LtnVrPilZXipWBLp3N32sGTP44E379um+aIQJyaVLvB+J8AvFkrkrqIbE+kz1xwgK4leobN0K/PZb3seoXh3qefNwePZs5Kxda1jjUFglSoife+Hrr3Fj837U5DX+h7e3uBZSk4hpdOyInDVrxNu8vHhNynvv8Y60AO/v4enJ30tKJb9dU3uaVz8VY7p1y/u9wZhj1JLIrclGKCEhQZuQ7Ny5E2+//TbCw8Mxbtw4nJFy9E65k/LDvSA1JLb+ZRAXJ+606uFhWV+HwggJAd56S1xzYKx2Q/gY6I9por8OGFbBAzzh6dGD/5I9dqzwfVjKlOGjYAprb4QJyRdf8PLdv6/bZklC4uKie70cP244CRuxnKl5USpV4l+6PXqYPSX8sypVwN5+2/YjPWv6WTg7W2cQx9KleRLVsSN/70yfbrAL69MH8c2b6za8+B4yqnZtXlty9SpP4AF+7BkzeFPWX3/lH1N+4/oAfG4huZNzk02ZMmUQ+2LG1L/++guvvBg6mjGGXDlMS2+vpExI7LGGZO5ccRVvfm3ItqZQAOvXQ92+Pf7WdCbV/Fcq+bKw2Ua/6QXgYz9UrSreJqwithX9L7OUFGDxYt26JQmJQiH+sqtbt/CTlRV3+v2kNPL6wpVa+/Z8lvBLlwxf06boXzHm5MTHAzp6lC+7ufGOtpcvG0/eAdzo00e3Mn9+3uerUkXcJ0yhAD7/nDdlde4MhIbmfX9zEhJHmGRSzjUkPXv2RL9+/dCpUyckJyejS5cuAIALFy6gmrGOVcQ8cqshOXbMttfi64/FIHVCAgDvvIPcvXvxSFOL0bMn/6V18iTvs/Lnn/zLv317XRWykKcn/9WWkMA75e7aZXycB2vz9jbcJny9WTrduLC6Pj0d2LmzQGGRF0z9yrbnhESh4J1XLWkGWbAAePll3vn04UPe/yMmJv+rhARSgoOhunCBJy2mLt03V373N+dyeEdISOyoD4nFc9n89NNPCA4ORmxsLGbOnImSL560hIQEjBD25ieW0U9IfvyRz1dh7DI8a9NPSBo04Nfif/BB3vfr2JFfDmiN6arT04FVq/ilrtWr86tShOwhIdHn5MR/aWm0bs3byfPqJOjiwn8Vfvqp7ePTMNb3RhijpQmJfnOAxNW8smeshkSpND0eiVzVq2c4zLtmbBJL1KlTsPvpe+mlvEd/NudzzRESEuFVshK/l81OSCZOnIgePXrgpZdewtixYw1u/+STT6wZV/Gj36l17FjebGHOZG2Fpd9ks307H78iv4Tk3DmeSFkyIZspP/zA5/BRKg0/JJydjbYp26X8rliQgv4cPgC/3FOjMDUkgH2WWU6MJSRffGGdRJ+Y1rOn8cutLeEICcm9e/y/p6fx2tQiZHaTTUJCAl577TUEBATg/fffx+7du2mIeGsy1mTzoq+OzeknJJZcBiq8fLQwNBMKqlT88j2NJk34XC00b0rBOTsbbhPOtGppQqL/RUmfAwV39SqwerXhdksHAiOWK1vW9DxVpua50U/u5Z6Q5OYC0dF8uUoVyZNgsxOSlStX4sGDB/jjjz/g7e2NiIgIlCtXDj179sSqVavwqABTSRMBe+rUaklCIhxgy1qEidjMmYUblIxw+uM4CNuNLU1IhLUrACUkBRUXxxPu27cNb7Pn/iOOJCLCcKJBwPQIz1u3ihN8uSck8fG6756i6B6QD4s6tSoUCrRp0wYzZ87E9evX8c8//6B58+ZYtmwZKlSogLZt22LWrFmIi4uzVbyOy546tWoSEnNGFrVWDYmQJmMHeNMRKbwvvzR9NZWlCYn+c57XMOLEtJ07TSdzjtZ/xJ4ZG9TQ1GXTjRrxjukach9CXvhZK7eERF/t2rUxbtw4/P3334iNjcXAgQNx7NgxrFu3zlrxFR/2lJBo3oxr15qeS0bDGjUkpi4XVyjol6K11K7NB5ozxtKERB/VkBSM8MtAqGFDyavOixX9hMTNLe/HXzjJntxrSITxG0vMipjVeqP5+vpi6NChGDp0qLUOWbxcvSrdufUTAs2b0cWFzzmRF2skJA8eGN9etap1OswSztTAcoVNSKiGxDKPH/P5ZfQvbQd4n4b83nPEuowlJHlxpIREOJ5UQcajsjKzEpKe+hMV5WHLli0FDqbY+vZbwFStklpt+xdKXvPo5HcFhTWabEyNVCkcqZUUnq0SEqohscwvvxhPRgDep4EULf2ExFgncCEPD/6ZrFbLf1BA4Y/R/MpdBMz6pitdurT2z8vLCwcOHMDZs2e1t587dw4HDhxAaYkHVZEtUx2oANPNGdZUmIn9rFFDojdbtFZh56UhYlRDYh+uXDG+/dtvizYOwumPZJxfkqFQ6EaAvXzZtgNE2pqdJSRm1ZCsXLlSu/z555/j7bffxpIlS+D8ogC5ubkYMWIEvGiAJOtTqawzCFBe8ktI5s/nc64YY40aElMJibH5YEjBeXpatt1cVENiGf1O/66ufBLJrl2liae4s3TSPYCPxHz9Ov9CP3xYPFOxnNhZk43FEaxYsQJjx47VJiMA4OzsjIiICKwQjh9hI4sWLUJISAjc3d0RGhqKY8eOmdw3ISEB/fr1Q82aNeHk5CTPwdsKU3tRkHMYG4Bs5Eg+PLoxtqwhqVmz8McmOi4uhlcPODlZPjrj1KnidaohsYz+hISzZ/MvNFv/8CDGBQUBLVtadh/hJH+3blk3nqJkZzUkFickOTk5uHbtmsH2a9euQW3jCdc2bNiATz75BF988QWioqLQpk0bdOnSBTEmRjPNyspC+fLl8cUXX6BhYWdRlYr+CK62oElI/PyA8eMNb1coTM9Ca40aEmNVpH5+ko8a6JD0JwwrU8byX0bjx/PZiTWohsR8arV49OWhQ/kfkZZw0j5zCCf/K4rRtG1F7gnJ4MGDMWTIEMyaNQvHjx/H8ePHMWvWLAwbNgyDBw+2RYxas2fPxtChQzFs2DDUrl0bc+bMQVBQEBYLZy4VCA4Oxty5czFgwAD59m8pyhqSvKruTXVutVUNyZAhhT8uMdS0qXi9IJf6KZVA7966dUpIzPf0qe5Hxquv8g6ulgxESGzD0h8/wuEIKCGxGosv+501axb8/f3x008/IeHFHAwBAQEYN24cPrXhhGHZ2dk4d+4cxuv9gg8PD8eJEyesdp6srCzRkPgpL6ZmVqlUUFmptkJzHM3/vCpqVenpNq8lccnJgQIAc3ZGjqlzqdVG48xNTYVa7z765cuP0+PH0LwVco4cAatalU8IVxS1QxaytGz2xiksDM7bt2vX1WXLIldQFrPL5+ysfT2o09NFx7Bnkj9/Dx7oHjdvb6s+bpKXzcZsWT6Fm5voyzDfc5QvDxcnJyjUaqhjYqzyPErx/ClUKm25cxkz+Cy3BkvKY3FC4uTkhHHjxmHcuHHaL+ui6Mz66NEj5Obmws/PT7Tdz88PiYmJVjvP9OnTMWXKFIPt+/btg2dhO//piYyMBBhDXt2hDkVGIkOvzNbWNTMTSgDPMzNxcPduk/u1r1QJXnq/Bm5duoTrJu4TGRlp1vnDzp5F4IvlIxcv4rkMLqUzt2z2xj8jA80E60k5OTht5PnLr3zuDx9CM89xwr17OJvH68YeSfX8ed+8iXYvlu+mpOCSDR43ub42zWWL8vleuYIWgvXdZjwv4WXKwCM5Garbt/GXFZ/Honz+KkVFofGL5UtXr+KeDV6P6RbUohdqYDQprqpR6I2gxxgz2FYYEyZMQIRgLICUlBQEBQUhPDzcauVVqVSIjIxEp06d8qwdAYD2bdoA1apZ5bymaF4EJb290TWvnv6hoQYjp1arUAFV9O4jKl9+HfWePIFS0GG27euvAwEBloRfpCwqmz0KDASmTdOu+taqJXrOzS6fYOyYgPxeN3ZE6udPIWj6rNyoEYKs+LhJXTZbs2X5FN7eos7a5ryenYODgeRkuKakoGvnzoVu8pDi+VPEx2uX6zVqhLo2eB9rKi7MUaCEZNOmTfjjjz8QExODbL0hz8+bGp66kMqVKwdnZ2eD2pCkpCSDWpPCcHNzg5uRkfqUSqXVXyRKpRLKfDqFKvmOVj2vgRftiIr8ylixIm/3/usv7Sbn7Gw4m7iPWY+Z3tU7yoAAWVxtYIvXQ5GoWlW06lSuHJyMlCPf8pUsqTuGSmX0GPZMsudP8OHsXL68yfdOYcj2tWkmm5SvZUs+b9a9e8D335t3fF9fAICCMShTU4Hy5a0SSpE+f4If8y5KpU0+ey0pi8WdWufNm4fBgwfD19cXUVFReOmll+Dj44M7d+6gS5culh7ObK6urggNDTWozoqMjERLSy/Zsif5XTJZlJ1a8xuVFTD8FVDYDo1JSbrlkSNlkYzImv4gUAWdvFCYtNNlv+YTXiKq/1wQ6SiVwNmzwJEjwNix5t1HmICYGm3a3tlZp1aLE5JFixZh6dKlWLBgAVxdXTFu3DhERkZi9OjReGbjEesiIiLwyy+/YMWKFbh27RrGjBmDmJgYDB8+HABvbhkwYIDoPhcuXMCFCxfw/PlzPHz4EBcuXMBVKeeN0ZffZbO27uCkVusGx5EiIRG+kTt2LNyxSP4UCnEtiaWXO2q4uup+XVFCYp7MTPHl0nYwmRkRKFeOT1dh7mXwL2pIAFBCYiUWN9nExMRoayQ8PDyQ+mJyof79+6N58+ZYsGCBdSMUeOedd5CcnIypU6ciISEB9erVw+7du1H5xa+8hIQEgzFJGjdurF0+d+4cfv/9d1SuXBl39QcnkorUNSSWviD136yFTUgePdItW6nKk+Tj++/5F+P77xe8v45CwYecT0+3zlg0xcHly+J1qiGRN0eoIRGOHSbHhMTf3x/JycmoXLkyKleujFOnTqFhw4aIjo4GY8wWMYqMGDECI0aMMHrbqlWrDLYVRUyFInUNifD45jSX2LKGhBKSotGrl3VmlNUkJNYYi6Y4uHdPvF6njjRxEOtwhIRE+INUjkPHd+jQATt27AAADB06FGPGjEGnTp3wzjvv4M0337R6gA5P6hoSYadkcxKSDh3E69ZMSPRHESX2TXMZPNWQmEeYkEyYQE02cidssrHi0BNFSu5NNkuXLtUOET98+HCULVsWx48fR/fu3bV9OYgF7KmGRH+eE2Pefx84cQL47Te+XpCERK3mV9fcugXs3cu3OTtTFbbcaBISqiExjzAhkcll0iQPjjB8vJwTkpycHHz33XcYMmQIgl6MR/H222/j7bfftklwxYLUNSSWNtm4uABr1hQuIVm8GBg1SrzN19cuqgyJBTw8+H+qITGPMCEp6NVNxH4In0N76ZNoKTnP9uvi4oIffvgBucKsihROfh/m9paQAPyFq7kipyAJiX4yAoh/bRB50NSQZGeLf2kR4zQJiYsLH6COyJuXl65WV64JiZ3VkFicEr3yyis4fPiwDUIppuypycaSMUA041BYmpCY6mRsTnMRsS+aGhIAeDGvFTFBrQYuXODLFSvaxYc/sYLgYP4/NrZoxoyyNjtLSCzuQ9KlSxdMmDABly9fRmhoKEqUKCG6/fXXX7dacMWC1E02lnZq1XBzA9LSLE9IYmONb5fjm7m4E87tFBQE9Ouna8ojYoMG6ZapNtBxaDq25uYCz59bPmuw1OysycbihOTDDz8EAMyePdvgNoVCQc05ltKvIZk0CRBO7mdvnVo1ClpDYqo3+ksvWXYcIj1hDQkA/P47719kB7+07M6vv+qWnz+XLg5iXcKkPD3dvhOSZ8/4e1Mw7YPsa0jUwoyKFJ6whmT5cmDwYODqVWDjRr7NHvuQAJYnJPfu8Q/l/fsNb6tSBfjqK/PPTeyDsdmvc3Ls4oPNriQni9cLOjousT/CpNyerza7dQto1IjXgly7BlSowLfbWUIifR1NcSesIfH15SNgduqk2+YofUhee40nHUeOiLevXMnfLD4+5p+b2AdjybKtX69ydOWKeP2DD6SJg1iffg2Jvfr0U97EnpoKfPyxbrscE5L169ebfcDY2Fj8/fffBQ6o2BHWkGiybeGcMraqIWEMuHlTfH5bJSRJSYbDZgPAnDm8bV0w4ySRkcePDbdRQmJImJAsWsSvziCOQZiQ2PPl78IpOoRXBNlZHxKzIli8eDFq1aqF77//HteuXTO4/dmzZ9i9ezf69euH0NBQPDb2QUWME76INQmJMDGw1Qf8xIlAzZpA9+66bQXpQ5KZqRvcDAAePDBMoi5dMn4MGipe3ighMY8wIalXT7o4iPXJpYZEePGJpg9TZqY8a0iOHDmCWbNm4eDBg6hXrx68vLxQvXp11K9fHxUrVoSPjw+GDh2K4OBgXL58Gd2FX3Ikb8IaCnd3/r8oakhmzOD/09J02wpSQwIAr77K+4hs2AAEBsKlWTMoNHHHxACvvGL8GPRLUd70+0YAlJAYI6wdrFtXujiI9ckxIUlLA95+m4+hsm6dbrsdJCRmd2p97bXX8NprryE5ORnHjx/H3bt3kZGRgXLlyqFx48Zo3LgxnOygykd28qshKcrLYQuakAB8OPkBAwC1GopLl+B3/jzw+uv8hW8KJSTy9t13hs8vJSRiOTnAv//yZX9/mr/G0cglIRFeWXP/vu6iCeEPYjv4/rb4KhsfHx+88cYbtoileBImJMZqSIryA96ShES/vVSpFCVPXtHRvJ/K6dOmj0EJibwZm0yTEhKxo0eBp0/5ctu2koZCbEB4lc3//gc0a2af48zojRdmlB3UkEifEhV3xjq1yqGGRL8vUUqK6P4lExLyn3CKEhJ5c3ExnP2ZEhKxQ4d0yz16SBYGsRFhDcmzZ8CXX0oXS170xwwyhhISYlc1JJZ0ah06VLyeksKrpDWHevYMihs38j4GJSTyp/+aoYRE7OZN3XKTJtLFQWxDfywe4QB4ReXsWcNLy/WZ88PWDhISi5tsSCFdvQqnRYsQevEiFOnp4k6lRVVDYmo+GUtqSL78EjhzRjeuyLNnost3XTIyoMhrwqnSpXUTUxH50n/NUEKik5kJ/PEHX3Z25gMAEsdibHDAonT8ONCmDe//cfkyULu28f3MeV/KsQ8JKaQHD+C8cCEqAlD7+QHCMVs0vzZtXUMinL9GyJKEpHRp4Ntv+ZsB4DUkgtoel4wMXWc+oenTeaeqESPsIiMnheSi9xFCCYnOTz/plkNCLHt/EXkwlpCo1UX35T5hgu6co0YBBw4Y38/UZ76QHXweW/yo0Uy/hVSunHbRadMm8W2aGgZbX/ZragAfSz8whU0uKSl8FMAXSt+7B+dlywzvM348sGABUKeOZeci9kl/UDtbJCRZWYav2dxcoFs3fhnt7dvWP6c1aGb3BUTNmcTB/e9/Rdf3T9g3JK8+e+a8L+WYkLz66quoWrUqvv32W8SamrmVmGbOYGC2HhjNFgnJ48f5z1xMHJ+1X6/37gGBgXzuDWET4J49wO7dfN6nnj2te05rSUrSLa9ZI10cxHYCAgy3rVgB/Pxz0ZxfMycNAMTHm97PnBoSO2iysTiC+Ph4fPzxx9iyZQtCQkLQuXNn/PHHH8g2p8DEvDlbbF1DYipxsKRTKyBOSOLi8t//++8tOz6xf9auIcnMFH94vvYaT3afPAF++IH3ufroI/F8HBcvFu6c1vb8ObB+PaCpTS5RgjfZEMdTu7bxK2t+/71ozi9MSEyNgxIfr+vLlBc51pCULVsWo0ePxvnz53H27FnUrFkTI0eOREBAAEaPHo1/jfUbIDpKJZixKao//1y0j5Zcmmzyqi789lsgKgr47DPLjk/kpzAJyf37QFAQ/5CNj+czQwtHOV20iN+2YAFw5474vvY0j8gHHwB9++rWfX2li4XY3jff8L5xQqYuHLA2cz6zR4ww71hyTEiEGjVqhPHjx2PkyJFIS0vDihUrEBoaijZt2uBKfpchFWeCfiRa776rW7Z1p1ZTNSSWviBdXPgXCAAkJBjfp2JFYOxYPvU1TaLn+Arzep08mU8C9ugRrwXZudNwn2fPjN83MbHg57U2/V/Hfn7SxEGKjnAkVEA8aZ0tmfOD9c8/zTuWHJtsAEClUmHTpk3o2rUrKleujL1792LBggV48OABoqOjERQUhN69e1s7VofBjDXbCHtrS1VDUpA+IK1b5337b78ZDjNPHId+klmY16swqTh/HoiONv++wtlMpSTo2K1FNSSOr1Qpac4rnBzPFHMTDTuoIbH4st+PPvoI615MyPPee+9h5syZqCeYwbJEiRKYMWMGgoODrRakwzFWQyJMSGxdQ2LNhCQsTDxBk76KFS0/JpGvwrxehYl6crK4E2t+jCUkjBV9rZywplOjatWijYEUPf2EpKiabMxJSNzdzZtnxw4SEotrSK5evYr58+cjPj4ec+bMESUjGoGBgTgkHDKZiDBjAyQVZQ2JqcSjIAlJfr8MAgMtPyaRL2slJKmphUtIPv2UH2/DhoLHk5eZM4HmzQ3natqxw3DfwYNtEwOxH/bcZKMZATw/ckxIJk2ahN69e8NV74qMnJwcHD16FADg4uKCdu3aWSdCR1SrluE2e6ghefVVy4+V34vd3DcDcQzWfL2mpPD/HTrwsR3yIkxIMjOB2bP5lTl9+lgvHmFcn3/Ok5Hmzfk2xviM10LlygELFwL161s/BmJf9H+YnT0LtGtn2NnVWh48ALZsMeyvZCwRMvcz2A76kFjcZNO+fXskJCTAV69d9NmzZ2jfvj1yzalCKuaYsUsAhbUieV32m5bGX4y3b/Pah7p1LQ/AWE3IoUMFG7wpjxc7q1sX1I21mClMQmKqWjkggCclxgba0xBe5ZWcXPAYzPHkiXidMWDxYmDkSN22ihUBGqep+NCvIQH4TM9Hj/LP89q1+UB+1mhCfPyYT0Ng7P2iUhn22XPkGhLGGBRGHtTk5GSUMGeKYwKW3zTkpppssrKAmjV5m3R4OL9yxdTVLXkRjvPQpQuvGn/5ZcuPAxi+2CtWRO6CBXhSvTpyadyR4qcwCYmpmjtf3/zH75kzRzcvlH7zjXC+KGvQ1NxozJolTkYAoGtX656T2Le8mq7HjQO6d9eNS1NYS5aYTt6Nvf9klJCYXUPS88VoiAqFAoMGDYKbIAvLzc3FxYsX0bJlS+tH6IhcXXH4xx/x8qefGr/dVJPNvn3iAchycvhVLGPHWnZ+YULSpw9QubJl9xfSf7H7+ED9/vs4WrEiuoaHF/y4RJ5sUUNiTkIC8CaS+/cNE5J796w7VYF+QjJunPFYSPFhzlU2ERF8PKbCEs4grc/YAKXC4eXzIqcmm9KlSwPgNSSlSpWCh6CQrq6uaN68Of6XXzsv0crMa6ZbUzUkxi6fLVvW8pMLX7SWjs6qTz8hKUg8RL6sOVJrXjUk1avnf//MTOC994BBg8Tb79yxbUJiDCUkxYuxJht9lo5mnpXFf5zq11zk1RRYXGpIVq5cCQAIDg7G2LFjqXmmkHLzylqFmarwBWbsRW9vCYk5v2SJ47JFDYmfH/8FOmtW/rWBf/0F1Kgh3nb1Kh+CHgAyMtDyyy/hMnkynw+nIP2mzElI6H1QvJgz1pIlCcnNm0DLlvx1f+ECn11dQzhHkr6CJiQKhV0MXFmgq2woGSm8nLwSAYVCV0sirCEx1mG4IJ2IqYaE2IqtakgAfinvqVPiwfj8/YHvvhPvP2+eeF0w143TvHkof/kyFBcuiKdryM+jR8DWrXyeGmMJSZUq4vcCjb9T/OTXb0h/uoO8jBqlG4tn2jTxbaZGKwaMJz3mJEt2UDsCmJmQNGnSBE9e9Cxv3LgxmjRpYvKPmMnZGblffMGvINi40fB2TT8S4Qe8sWvOC/IFQDUkxFqs1WRz/z5PNowRDrLYrJl45FMXF2DiRH7li6lmUEFCohCe4+BB8+Pr1o3PKjxihPHRWN94g5+nfXs+OFpBO4kT+dq6lV/uK5z4UUit5lcz5uf5cyAyUrd+44ZumTF+laUpxt5/5iQbdtB/BDCzyeaNN97QdmLt0aOHLeMpVtSTJsH5m2+MV5VpEhJhEmIsISnIwGnChMTSCfX0UQ1J8fb55+KZRAuakHzzjfHt/v5A+fLibcLXvOZ94u3Nk4EtWwyPcekS0KIFEBICp127dNvv3+fNOfn1L0lLA/75hy//+iuvDdH3+uu8n4slSQ5xLK6uQGgov/jAlNGj+evRBEVODlxCQ8UbhU2ZKSl5N/0Yu82cWnQ7qSExKyGZNGmS0WViBaba7TSJAtWQEHvWpAnw/fe65o+CjPYL8F+XxrRoYbjNWEICiGtS9J06ZbwGZtgwwwHN9N27J143Ns5JfnM6keLD2GzuGpcvA3//DaxZAwwfDjRuLLq57PXrUOjP4SS8bD2v2hEAOH6cNxcKawvN+dFqJwmJxfU0Z86cwWn94ZIBnD59GmfPnrVKUATGa0iMZbqFrSGhPiSksN54Q7dsrDkjP5cvAw8fGr/NWPW3qYSkIJevnzyZ/z76Q9gvWCBenztXHAcp3po2NX2bQsGvBFu6lCexerNUOxn7gSmsIckvIRkxAmjQQPxD1ZoT8NmYxVGMHDkSsUYuO4qLi8NI/cGBSMEZ69RKNSTEHgnHYLAkIVGrgb59jQ+tPmoU8PQpH35bX4UKumXhxHUFndDTWB8uIf0aEqFnz3g1PCEaYWGmkxLGdAluejrw55+im53+396dx0VVLnwA/w27gowKsqkImrnvZuGS4YJlpt5u5ZZJlkplmvaWYvWqdcvqtlia5XWtqzez1+VmmUrX/eKSKO7hhiIJubIkigPzvH+MM5yZOTPMgdn5fT8fPjDPHA7PA8Phx3OeRS48SAd7W5tho5ebC2RkVDy25343DlalzfXkBq926tQJJ06csEulCLYPanV1D4npf4bsIal5qhpIvv8eWLXKvDwnB5g3z3iqo9S77+qCr1pt3FvRrRtQlRmATz2l+8/V5I+DgaV1H4KCgNBQ5V+PvN9HH9l2nL6H5M4dqA4cQIDc78/VqxW7B1+/btt5pTNrbOkhsXXxNAdTHEgCAwPxh0y3UV5eHvyc0G25YMECxMfHIygoCF26dMGuXbusHr9jxw506dIFQUFBaNq0Kb766iuH19EuPKWHxBR7SGqe4OCKsVBKAol+oKhUgwZA48bWPy86Wvdf4KVLxr0iUVHAr78Cr7yim3nzxBO21wUARo/WzXCQWrTI8gZpb7+t7PxUc9j6B15/q3L4cPh1747On31mfsy1axVbhBQUKK+LLf+0emog6d+/P1JTU1EomQtdUFCAGTNmoH///natnKnvvvsOr7zyCt544w0cOnQIvXr1wiOPPIIc6cZaEtnZ2Rg4cCB69eqFQ4cOYcaMGZg0aRLWrFnj0HrahadM+zVlbQVa8k4+PhWL9tmyaJieXG+GdNdra4KC5I9t1Qr49FNdL4rcJpZ3CbUa6NHDuLC4GPi//6t4fPYsMH68/AmGD9ctBU4kx9ZbIFev6nowLA3q1tMvOS/d2NHa1ygtrfhY/3fDx8fy4FVPDSQff/wxLl68iCZNmiAxMRGJiYmIj49Hfn4+Pv74Y0fU0eCTTz7Bc889h+effx6tWrXC3Llz0bhxY3z55Zeyx3/11VeIjY3F3Llz0apVKzz//PMYO3YsPrK1O82VbF0YrSq3bKQhxt6BxN7nI8+gv22jpIdELpDou6btwcq5RLduwK5dui5w/SqugNGaJUYfSzVsqJsl4SYzE8gN2foH/rvvgMOHKz9OvxaJNJBER1s+XvpPp/7vhp+f5UXS3CSQKL7H0rBhQxw5cgQrV67E4cOHUatWLTz77LMYMWIE/Ku7poUVd+7cQUZGBqZPn25UnpSUhHQL0/b27NmDJJMN3gYMGIAlS5ZAo9HI1re0tBSlknRZdPc/Po1GA011VqGU0J/H2vn8fH2hAiA0GpTdPU5VWmr2Ayu/fRtahfXyLS01JFGNSlW91TUB+D72GHw2bIC2f3+US75P9vp+uRNvbhtQ9fb5hYToXq/FxYbXa2V8AgJg+ie9fMAAxa9nS3yvXbP4H5fw8YGmrEzXszNvHvx//BEAoD14EOX63zet1vz3bepUaIcN0z1ws9cAX5tuxNcX0r8u5c8/D9/Fi+WPNV13REb51avQajRGr2ltZCR8TKcI31V28ybE3e+Tn0aj+9309QUCA6GS2aJBGxRkeN3bm5KfV5UGfQQHB2O8pa5MB7l69SrKy8sRGRlpVB4ZGYl8k6lTevn5+bLHl5WV4erVq4iWSZhz5szB7Nmzzcq3bNmC2rZ2J9soTboan4kHb95EPQAoK8PGjRsBAE0yM9HR5LizWVk4efd5W3W/dAn6paY2b9uG8mqOsPYbMQINWrXC1fbtoZHUxVr7PJ03tw1Q3r4HtVrd6/XPP7Hxp59s2hej2dGjaCt5nN+1Kw716IE7Cl/PlnT4/XfEWXju8o0b2K//Olot9BOXfXbsQPoHH+Bau3ZovHMnTIfv//jgg7r7+fp7+m6Ir03XCygqwiOSxzvat0efapwvJzMTv/3rX7jvxAnot23MBxBj4fgD//0v/rhzB/5//omBx44BAMoAlAOQu9r/UVxc8ftgZyWW9qiSUaVAcvbsWcydOxcnT56ESqVCq1atMHnyZDSTTsFzEJXJhU4IYVZW2fFy5XqpqamYKrk3XFRUhMaNGyMpKQmhdhpRr9FokJaWhv79+1vsVfL94APg9GmohMDAAQMAX1/4yEw/bBYbi/jK9lAwPbfkltWAxx6r/mqtgNEAQlva56m8uW1A1dvn+9lnwJkzUGm1GPjQQzbNdvExuSUStnQp+rVsqbTKlrVoAdGmDVRardlT4YmJGCj5vRH160N1dwZD9+xslE+bBp+zZ80+b6DC3zVn4mvTjZSXQ7zxBlQXL6J83Dj0SkmBeOcdqCytt1OJuL17Ef/zz4bHQqVCZIcOFrdb6Nq+PcRDD8GvVStDmV9AAPxCQ41v+9wV2aSJw17bRQrGlSkOJJs3b8bgwYPRsWNH9OjRA0IIpKeno02bNtiwYYPDBraGh4fD19fXrDfk8uXLZr0gelFRUbLH+/n5IczCbJDAwEDDMvlS/v7+dv8lsHpOSbm/dLM9E75CwFdpvSRdaP61ajlsl0dHfM/chTe3DahC+yRh3f/WLeurVeqZdOX6h4fbJxzrtWwJnD6tW+9h2DDdMvEACuPiUHvaNOP2PfMMMHcuAMAnOxs+/v6y42E84WfO16Yb8PfXrZqang7fwYN11+iFC3X7IdmiQwfg66+Bjh0BACqTEKFSq+ErnW5vwq+8XDfuRNKTpyos1O2cLcMnOFj3mncAJT8rxYNap0+fjilTpmDfvn345JNP8Omnn2Lfvn145ZVXME3J7pkKBQQEoEuXLmbddWlpaejevbvs5yQkJJgdv2XLFnTt2tUzXtB6+oGr9p5lExDgFltOkxeQXugsrdthynSZedM9a+yhaVOgbVvg4EHg7FloSkux/dNPK2YF6UkH5Osv/lWZYkmkFxurm42lv9Uv3RQSAN54Q/e+USMgOdn4ueef1y0YaOn6HBpqfUbanTvGS87rWRrU6qkrtZ48eRLPPfecWfnYsWMdvjDa1KlTsXjxYixduhQnT57ElClTkJOTg5SUFAC62y3PPPOM4fiUlBRcuHABU6dOxcmTJ7F06VIsWbIE//M//+PQetqFdE0XfehwRCAhsod77634+NQp2z5HGkiWLHHs8uuBgbpwolLJX+R9fCrWP8nM1E0bNt0EbdYsx9WPvJ9pIJk9G/jPf3Rr55iuvRMbq3tNWgokdepYvy1aWqoskFjbsM+JFF8BGjRogMzMTDRv3tyoPDMzExGm33A7GzZsGK5du4a3334beXl5aNu2LTZu3Igmd/ewyMvLM1qTJD4+Hhs3bsSUKVPwxRdfICYmBp9//jn++te/OrSedmFrD0l1Vmp1914i8hzSQKKfolhWZj1kSNdKsLb/h7PExFT07rz5pvFz//qXbkVXoqoy/fvo6wv0uTvU1XRVYv2+TDLjnwDoevgqCyRyg0ktBRLp76ILKQ4k48aNw/jx43Hu3Dl0794dKpUKu3fvxgcffIBXX33VEXU08uKLL+LFF1+UfW758uVmZb1798bBgwcdXCsHkOshkVuHhD0k5A6kgeTMGd0f8AkTgDFjzDej05P2kLjDXhoxluYsABg6lOuOUPWo1bpetlWrdFsjSJlOmNAHkgcfBHbuND9XSIh9b9l4ag/JW2+9hTp16uDjjz9GamoqACAmJgazZs3CJG4yZT/O6CFhICF7kQ4SLy4GRo3SffzFF7p9PeQCh7sFkqQk+RUz/f3dZuEo8nAzZ+reTHXqZPhQtGwJlb7H5J13dCFGo9ENktWrrIfk8mX58OHmgUTxGBKVSoUpU6YgNzcXhYWFKCwsRG5uLiZPnmx1+i0pxDEk5Emkf7Clu5MClkOzuwWSsWPly3ldI0fr2hVlmzfj+JgxKFuzpuI19+CDwNatwMsvGx9fWQ/Jhx/KrzTsbYFEqk6dOqhjZeoRVYM0kLCHhNydNFB4aiAJCNBtsEfkAiIxEWf+8hfAZHwmAPMeusp6SADdxpCmLAUS/erDLmbTLZtOnTrZ3PvhkeM13JHcLRuOISF35eure81qNOaBxNJr1N0CCQDod1tdu7biHrybXKypBjPtDamsh8QSaSAJDNTtjK1SWe4ddDKbAsnQoUMdXA0yw1s25Glq1dK9Hk3XF6kskFhZ+M/p6tXTbZy3eDHw5JO67eE//NDVtaKazrSHJDjYptWQzUgDiUoFvP9+9eplZzYFkplyg3DIsWwd1Kr03l95ecUuqAwkZE+1agFFRcp7SIKC3G+cRkAA8O9/u7oWRDpyt2yq0kMivebL9bi7WJXGkBQUFGDx4sVITU3F9bv7Pxw8eBC///67XStXo9naQ7JtG3D1qu3nlQYYBhKyJ/1FU2kgsXRfm4h05G7ZmPaQzJhR+Xnkxia6EcWB5MiRI7j33nvxwQcf4KOPPkLB3eWV161bZ5gGTHZgaw8JYD6n3RoGEnIU/TgQWwe16hdjcpfxI0TuypZBrbaMA5EGEn1PuRtRHEimTp2K5ORknD59GkGSC8kjjzyCnXILuFDV2LowGgBkZ9t+XgYSchT9RVPpGBIGEiLrTANJWJh5mS23cBy5PYMdKA4kv/76KyZMmGBW3rBhQ7OddakabJ32CxgvSlUZBhJyFP0F0jSAMJAQVY9p+HjgAd3MNv2Ek3ffBaKjgenTrZ/HzVcbVhxIgoKCUFRUZFaelZWFBo7YrbOmkt6ysTaGBKjYndQWDCTkKJZWM2UgIaoe09+t+vV179euBXJyKsaPzJmjuxVjupu1nrf1kAwZMgRvv/02NHcvMiqVCjk5OZg+fbpnbFrnKSrrIdm8ueJjDmold6AkkAjBMSREtvL11a2R07kzkJZWUa5Sme8UDABRUeZl3bp5XyD56KOPcOXKFURERODWrVvo3bs37rnnHtSpUwfvvvuuI+pYM1W2MFrr1hUfVzWQuMvaD+QdLAULuUAi3V2UgYSocpMmARkZQL9+lR9rulnfSy8Bq1e7fSBRXLvQ0FDs3r0bW7duxcGDB6HVatG5c2f0s+WbRLarbNpvYKBuEacbN4Br12w/L3tIyFGU9JC44yqtRN5CuqVL8+YVO257WyA5f/484uLi0KdPH/Tp08cRdSKg8mm/fn66+4gMJOQuqhpIuA4JkX1Jx5BIe9bdPJAovmXTtGlT9OzZEwsXLjQsikYOUFkPiZ9fxYVcyfLxDCTkKOwhIXIP0r8fWm3Fx942y+bAgQNISEjA3/72N8TExGDIkCH4/vvvUSq9J0zVV1kPia9vxYtOyYp7DCTkKErGkDCQEDmOj+RPu7SHxNsCSefOnfH3v/8dOTk5+PnnnxEREYEJEyYgIiICY91kx0CvINdDUlyse+/jo7uIVyWQSIMjAwnZk5IeEg5qJXIcafDw5ls2eiqVComJiVi0aBF++eUXNG3aFF9//bU961azyU371a83Uq+eLpToj7F1k6QDB4DHHqt4zEBC9sRbNkTuoaYFkosXL+LDDz9Ex44dcd999yE4OBjz9SN5qfrkFkbTj9nRL4qjf3EJYXyf0BLTQcgMJGRPDCRE7sFSIJHOvnFDiuPSP/7xD6xcuRL//e9/0aJFC4waNQrr169HXFycA6pXg5n2kGi1wN2NDFGvnvwxlQUM/S0fPQYSsidLgUTuliIDCZHjSMeQSP9Z/ctfgPh44Px5YN06p1erMooDyTvvvIPhw4fjs88+Q8eOHR1QJQJg3ENy+zYwe3bF7oymPSSAbYHEFAMJ2RMHtRK5h8jIio8bNar42N8fOHkSuHLFuNxNKA4kOTk5UKlUjqgLSUnDxvr1wKFDFY8tBRKlGEjInmy9ZVNeDnz7bcVjrkNCZF+pqcCyZcDNm8Dy5cbPBQa6ZRgBqhBIGEacRNpDIg0jAFBSonvPQELuxNZAsmIF8N13FY/ZQ0JkX2FhwMWLwK1bynaDdzH3HnJbk1kbDa0PHwwk5E5sDSTJycaPGUiI7K92bd2bB6nyLBtyMGsb302erHvPQELuRMkYEls+j4hqFEWBRAiBCxcu4NatW46qD+mZzojR++STit0epVO7Kgsk0kGEetztl+xJybRfKQYSIkIVAknz5s2Rm5vrqPqQXvv28uVdu1Z8rKSHRD9lWIo9JGRPDCREVA2KAomPjw+aN2+Oa0p2l6WqiYkBRowwL5fOSFASSAoLzcsYSMieGEiIqBoUjyH58MMP8dprr+HYsWOOqA9JPfeceZk0RCgJJHK3bBhIyJ4sBZLKbvEykBARqjDL5umnn0ZJSQk6dOiAgIAA1DK5CF3XL29O1deggXlZVXtI5HZjZiAhe7IULCyNh9LjOiREhCoEkrlz5zqgGiQrOtq8jIGE3JWlHpKiIuufxx4SIkIVAsmYMWMcUQ+S06ABULeu8YBUBhJyV35+utfUnTvG5QwkRGSDaq1DcuvWLRQVFRm9kZ19+qnxY0tjSKQ7OsphICFnCAkxL2MgISIbKA4kN2/exMSJExEREYGQkBDUq1fP6I3szHSlPUs9JGfOVGy+J4eDWskZpGvj6DGQEJENFAeS119/HVu3bsWCBQsQGBiIxYsXY/bs2YiJicE333zjiDrWbLYGkmeeAbp1s9xTwh4ScgYfmUuK3JRzKQYSIkIVAsmGDRuwYMECPPHEE/Dz80OvXr3w5ptv4r333sPKlSsdUceazXSgoKVbNgBw4ABw/Lj8eRhIyBnkNt8sKrLee8dZNkSEKgSS69evIz4+HgAQGhpqmObbs2dP7Ny50761I/MeEukFX24DPkvTrhlIyBnkekjKyuRvGerJ3eYhohpHcSBp2rQpzp8/DwBo3bo1Vq9eDUDXc1K3bl171o0A67s1Kgkk3MuGnEEukACVjyMhohpPcSB59tlncfjwYQBAamqqYSzJlClT8Nprr9m9gno3btzA6NGjoVaroVarMXr0aBTI7c8isXbtWgwYMADh4eFQqVTIzMx0WP0cpqqBRAjg0KGKx3I9JHLd60TVYSmQ3Lype1/ZbDAiqrEUr0MyZcoUw8eJiYn47bffcODAATRr1gwdOnSwa+WkRo4cidzcXGzatAkAMH78eIwePRobNmyw+Dk3b95Ejx498OSTT2LcuHEOq5tDVTWQfPMNkJwMREQAFy7IBxIie2vTBsjJMS/XanXv+TokIgsUBxJTsbGxiI2NtUddLDp58iQ2bdqEvXv34v777wcALFq0CAkJCcjKykKLFi1kP2/06NEAYLjF5JEsrX4JWA8kycm695cvA7/8wj8E5BwLFgB3x5gZ0QcSa2NJiKhGsymQfP755zafcNKkSVWujCV79uyBWq02hBEAeOCBB6BWq5Genm4xkFRFaWkpSiV/vPWLvWk0Gmgq27XURvrz2HQ+f39IR3pIP8dHpYLpcEDt1aso12iMPqfMxweqkhKzY+3VHlOK2udhvLltgB3a17Ah/Dp1gurQIePzlpbqdv0tLobpyCVnfi+9+efnzW0D2D5PpaQ9NgWST01XC7VApVI5JJDk5+cjIiLCrDwiIgL5+fl2/Vpz5szB7Nmzzcq3bNmC2tZun1RBWlpa5QcJgSGShxs3bjR83OTkSXQ0OTz/xAn8unGj0efsOXIEDU+dQlOTY6XncgSb2uehvLltQPXa1/P2bYSZlO3asQPF586hdn4++kvKT4wahdMOfh3K8eafnze3DWD7PE1JSYnNx9oUSLKzs6tcGWtmzZol+8df6tdffwWgCzumhBCy5dWRmpqKqVOnGh4XFRWhcePGSEpKQmhoqF2+hkajQVpaGvr37w9/G2a6aJOS4LNlC8qnTMHAgQMN5ao//jA7Nqp2baNjACAhIQE+p0+bHWt6nL0obZ8n8ea2AfZpn+/cucDJk0ZlvXr0ANq2BU6cMJRpH3sMzZctQ/PqVFghb/75eXPbALbPUynZUqbaY0iqY+LEiRg+fLjVY+Li4nDkyBH8IfPH98qVK4iMjLRrnQIDAxEos1CTv7+/3V8kNp/zxx+B48fh26EDfKUBTKaePiUl8DE5px+g6y6X+fqO5Ijvmbvw5rYB1WyfzPo2/n5+umnmklk2Po0bm71WncWbf37e3DaA7fM0StqiOJCMHTvW6vNLly61+Vzh4eEIDw+v9LiEhAQUFhZi//796NatGwBg3759KCwsRPfu3W3+eh7L3x/o2NG8XG5Q659/mpdpNBxMSM4jdwGSG9TKJeOJSEJxILlx44bRY41Gg2PHjqGgoAB9+vSxW8WkWrVqhYcffhjjxo3DwoULAeim/Q4aNMhoQGvLli0xZ84c/OUvfwGgW1U2JycHly5dAgBkZWUBAKKiohAVFeWQujqV3AqXN2+ah4+yMs6yIeeRC8oMJERUCcWBZN26dWZlWq0WL774Ipo2NR02aT8rV67EpEmTkJSUBAAYPHgw5s+fb3RMVlYWCiUbef3www949tlnDY/1t4dmzpyJWbNmOayuTiN3b+7mTcAkNFa6dDeRPTGQEFEV2GUMiY+PD6ZMmYKHHnoIr7/+uj1OaaZ+/fpYsWKF1WOEyQZeycnJSNavx+GN5GYY3bwJmK5gq9EAt245pUpEvGVDRFWheOl4S86ePYuysjJ7nY5s0aSJednNm4DpNKuyMuMyPz9AwVgfIkXGjDEvYyAhokoo7iGRTokFdL0SeXl5+OmnnzBG7kJEjjNyJLB6NfDHH7rbN6dP6/awMe0hkQaSOnWAS5eAkBCnV5dqiAEDgIULgQkTKsoYSIioEooDySGTFRh9fHzQoEEDfPzxx5XOwCE78/cHfvpJ9/GgQbpAAgBXrxofJ71lU7s2wwg5lkoFjB8PnDoFfPyxroyBhIgqoTiQbNu2zRH1oOoKDq742DSQSHtIrO2NQ2RP0jVztFpdz928eRVlDCREJGG3MSTkYtJAcu2a8XMaTUUgsfPy90QW+UguL1ot8OKLwG+/VZQxkBCRhOIekk6dOsku165SqRAUFIR77rkHycnJSExMtEsFyUbWekgYSMgVTAPJt98aP89AQkQSintIHn74YZw7dw7BwcFITEzEQw89hJCQEJw9exb33Xcf8vLy0K9fP/z73/92RH3JEmkguXLF+Llbtyru4TOQkLNIA4nJlHwADCREZERxD8nVq1fx6quv4q233jIq/9vf/oYLFy5gy5YtmDlzJt555x0MGTLEwlnI7qQrz546ZfycZLE4BhJyGtMeElMMJEQkobiHZPXq1RgxYoRZ+fDhw7F69WoAwIgRIwzLtJOTtGxZ8bHJTCijFV05qJWchYGEiBRQHEiCgoKQnp5uVp6eno6guxcYrVYru2MuOZBkTx+z7nFpIGEPCTmLNJAcOWL+PAMJEUkovmXz8ssvIyUlBRkZGbjvvvugUqmwf/9+LF68GDNmzAAAbN68GZ06dbJ7ZcmK2FjdBV5uzxoGEnIFaSB57TXz5xlIiEhCcSB58803ER8fj/nz5+Of//wnAKBFixZYtGgRRo4cCQBISUnBCy+8YN+aknW+vsC998r/J8oxJOQKPpV0wDKQEJFElTbXGzVqFEaNGmXx+Vocp+AaLVvKB5KtWys+ZiAhZ2EgISIFqrzb7507d3D58mVoTQarxcbGVrtSVEXSga2WDB7s+HoQAQwkRKSI4kBy+vRpjB071mxgqxACKpUK5eXldqscKSS3+6/U1KnAAw84py5EMgsoGvGr8v9DROSFFF8RkpOT4efnhx9//BHR0dGyq7aSi0gXR5PTu7dz6kEEVN5DwmsHEUkoDiSZmZnIyMhAS1tuD5BzVRZI6td3Tj2IgMoDCRGRhOIrRuvWrXHVdK8Ucg+VDVitV8859SACGEiISBHFV4wPPvgAr7/+OrZv345r166hqKjI6I1ciIGE3AkDCREpoPiWTb9+/QAAffv2NSrnoFY3wEBC7oSBhIgUUBxItm3b5oh6kD1YCyRBQdzHhpyLgYSIFFAcSHpbmamRmZlZnbpQdVkb1MreEXI2BhIiUqDaV4zCwkIsWLAAnTt3RpcuXexRJ6oqaz0knGFDzsZAQkQKVPmKsXXrVjz99NOIjo7GvHnzMHDgQBw4cMCedSOlrAUS9pCQszGQEJECim7Z5ObmYvny5Vi6dClu3ryJp556ChqNBmvWrEHr1q0dVUeylb+/5ecYSMjZGEiISAGbrxgDBw5E69atceLECcybNw+XLl3CvHnzHFk3sifesiFn40qsRKSAzT0kW7ZswaRJk/DCCy+gefPmjqwTOQJ7SMjZ2ENCRArYfMXYtWsXiouL0bVrV9x///2YP38+rly54si6kT0FBLi6BlTTWAskPXs6rx5E5BFsDiQJCQlYtGgR8vLyMGHCBKxatQoNGzaEVqtFWloaiouLHVlPstXQobr37dsbl5eVOb0qVMPJBZK6dYHBg4EVK5xeHSJyb4r7VGvXro2xY8di9+7dOHr0KF599VW8//77iIiIwODBgx1RR1Ji8WJgyRJg40bjcq6gS84mF0jeew/497+BJk2cXx8icmvVusnbokULfPjhh8jNzcW3335rrzpRdYSFAWPHAg0bAsnJFeXdu7usSlRDyQWSwEDn14OIPILilVrl+Pr6YujQoRiqv11A7uGjj4CiIiAqCnjiCVfXhmoauUDCsUxEZIFdAgm5qbAwYM0aV9eCaiq5QOLHSw4RyeO8PCJyDLlA4uvr/HoQkUdgICEix2AgISIFGEiIyDHkVmrlLRsisoCBhIgcgz0kRKQAAwkROQYDCREpwEBCRI7BQEJECnhMILlx4wZGjx4NtVoNtVqN0aNHo6CgwOLxGo0G06ZNQ7t27RAcHIyYmBg888wzuHTpkvMqTVSTcdovESngMYFk5MiRyMzMxKZNm7Bp0yZkZmZi9OjRFo8vKSnBwYMH8dZbb+HgwYNYu3YtTp06xeXtiZyFPSREpIBH/Lty8uRJbNq0CXv37sX9998PAFi0aBESEhKQlZWFFi1amH2OWq1GWlqaUdm8efPQrVs35OTkIDY21il1J6qxGEiISAGPCCR79uyBWq02hBEAeOCBB6BWq5Geni4bSOQUFhZCpVKhbt26Fo8pLS1FaWmp4XFRUREA3S0gjUZTtQaY0J/HXudzN97cPm9uG2Df9qm0WrMLTJkQEC783nnzz8+b2wawfZ5KSXs8IpDk5+cjIiLCrDwiIgL5+fk2neP27duYPn06Ro4cidDQUIvHzZkzB7NnzzYr37JlC2rXrm17pW1g2oPjbby5fd7cNsA+7Qs7fhw9Tcr+u28fCq5dq/a5q8ubf37e3DaA7fM0JSUlNh/r0kAya9Ys2T/+Ur/++isAQCWzyJIQQrbclEajwfDhw6HVarFgwQKrx6ampmLq1KmGx0VFRWjcuDGSkpKsBhklNBoN0tLS0L9/f/j7+9vlnO7Em9vnzW0D7Ns+lVptVta9Vy+gU6dqnbc6vPnn581tA9g+T6W/y2ALlwaSiRMnYvjw4VaPiYuLw5EjR/DHH3+YPXflyhVERkZa/XyNRoOnnnoK2dnZ2Lp1a6WhIjAwEIEyW6T7+/vb/UXiiHO6E29unze3DbBT+2R29vUPCgLc4PvmzT8/b24bwPZ5GiVtcWkgCQ8PR3h4eKXHJSQkoLCwEPv370e3bt0AAPv27UNhYSG6d+9u8fP0YeT06dPYtm0bwsLC7FZ3IqqEXO8lB7USkQUeMe23VatWePjhhzFu3Djs3bsXe/fuxbhx4zBo0CCjAa0tW7bEunXrAABlZWV44okncODAAaxcuRLl5eXIz89Hfn4+7ty546qmENUcXIeEiBTwiEACACtXrkS7du2QlJSEpKQktG/fHv/85z+NjsnKykJhYSEAIDc3Fz/88ANyc3PRsWNHREdHG97S09Nd0QSimoXTfolIAY/5d6V+/fpYsWKF1WOEEIaP4+LijB4TkZMxkBCRAh7TQ0JEHoaBhIgUYCAhIsfgGBIiUoCBhIgcgz0kRKQAAwkROQYDCREpwEBCRI7BQEJECjCQEJFjcAwJESnAQEJEjsEeEiJSgIGEiByDS8cTkQIMJETkGOwhISIFGEiIyDHkVkpmICEiCxhIiMgxysvNy+Ru4xARgYGEiBxFLpAQEVnAQEJEjsFAQkQKMJAQkWP4+7u6BkTkQRhIiMgx7r0XaNLE1bUgIg/BQEJEjqFSAbt2uboWROQhGEiIyHF424aIbMRAQkSOw71riMhGDCRE5DhcCI2IbMRAQkSOwx4SIrIRAwkROQ57SIjIRgwkROQ47CEhIhsxkBCR47CHhIhsxEBCRI7jw0sMEdmGVwsichzu7ktENmIgISLH6t5d9378eNfWg4jcGkecEZFjbdwI7N0LPPSQq2tCRG6MgYSIHEutBgYMcHUtiMjN8ZYNERERuRwDCREREbkcAwkRERG5HAMJERERuRwDCREREbkcAwkRERG5HAMJERERuRwDCREREbkcAwkRERG5HFdqrYQQAgBQVFRkt3NqNBqUlJSgqKgI/v7+djuvu/Dm9nlz2wC2z5N5c9sAts9T6f926v+WWsNAUoni4mIAQOPGjV1cEyIiIs9UXFwMtVpt9RiVsCW21GBarRaXLl1CnTp1oLLTVupFRUVo3LgxLl68iNDQULuc0514c/u8uW0A2+fJvLltANvnqYQQKC4uRkxMDHx8rI8SYQ9JJXx8fNCoUSOHnDs0NNSrXnimvLl93tw2gO3zZN7cNoDt80SV9YzocVArERERuRwDCREREbkcA4kLBAYGYubMmQgMDHR1VRzCm9vnzW0D2D5P5s1tA9i+moCDWomIiMjl2ENCRERELsdAQkRERC7HQEJEREQux0BCRERELsdA4gILFixAfHw8goKC0KVLF+zatcvVVarUzp078dhjjyEmJgYqlQrr1683el4IgVmzZiEmJga1atXCQw89hOPHjxsdU1paipdffhnh4eEIDg7G4MGDkZub68RWyJszZw7uu+8+1KlTBxERERg6dCiysrKMjvHk9n355Zdo3769YcGlhIQE/Pzzz4bnPbltpubMmQOVSoVXXnnFUObJ7Zs1axZUKpXRW1RUlOF5T26b3u+//46nn34aYWFhqF27Njp27IiMjAzD857axri4OLOfnUqlwksvvQTAc9vlUIKcatWqVcLf318sWrRInDhxQkyePFkEBweLCxcuuLpqVm3cuFG88cYbYs2aNQKAWLdundHz77//vqhTp45Ys2aNOHr0qBg2bJiIjo4WRUVFhmNSUlJEw4YNRVpamjh48KBITEwUHTp0EGVlZU5ujbEBAwaIZcuWiWPHjonMzEzx6KOPitjYWPHnn38ajvHk9v3www/ip59+EllZWSIrK0vMmDFD+Pv7i2PHjgkhPLttUvv37xdxcXGiffv2YvLkyYZyT27fzJkzRZs2bUReXp7h7fLly4bnPbltQghx/fp10aRJE5GcnCz27dsnsrOzxS+//CLOnDljOMZT23j58mWjn1taWpoAILZt2yaE8Nx2ORIDiZN169ZNpKSkGJW1bNlSTJ8+3UU1Us40kGi1WhEVFSXef/99Q9nt27eFWq0WX331lRBCiIKCAuHv7y9WrVplOOb3338XPj4+YtOmTU6ruy0uX74sAIgdO3YIIbyvfUIIUa9ePbF48WKvaVtxcbFo3ry5SEtLE7179zYEEk9v38yZM0WHDh1kn/P0tgkhxLRp00TPnj0tPu8NbdSbPHmyaNasmdBqtV7VLnviLRsnunPnDjIyMpCUlGRUnpSUhPT0dBfVqvqys7ORn59v1K7AwED07t3b0K6MjAxoNBqjY2JiYtC2bVu3a3thYSEAoH79+gC8q33l5eVYtWoVbt68iYSEBK9p20svvYRHH30U/fr1Myr3hvadPn0aMTExiI+Px/Dhw3Hu3DkA3tG2H374AV27dsWTTz6JiIgIdOrUCYsWLTI87w1tBHTX/hUrVmDs2LFQqVRe0y57YyBxoqtXr6K8vByRkZFG5ZGRkcjPz3dRrapPX3dr7crPz0dAQADq1atn8Rh3IITA1KlT0bNnT7Rt2xaAd7Tv6NGjCAkJQWBgIFJSUrBu3Tq0bt3aK9q2atUqHDx4EHPmzDF7ztPbd//99+Obb77B5s2bsWjRIuTn56N79+64du2ax7cNAM6dO4cvv/wSzZs3x+bNm5GSkoJJkybhm2++AeD5Pz+99evXo6CgAMnJyQC8p132xt1+XUClUhk9FkKYlXmiqrTL3do+ceJEHDlyBLt37zZ7zpPb16JFC2RmZqKgoABr1qzBmDFjsGPHDsPzntq2ixcvYvLkydiyZQuCgoIsHuep7XvkkUcMH7dr1w4JCQlo1qwZvv76azzwwAMAPLdtAKDVatG1a1e89957AIBOnTrh+PHj+PLLL/HMM88YjvPkNgLAkiVL8MgjjyAmJsao3NPbZW/sIXGi8PBw+Pr6mqXby5cvmyVlT6If9W+tXVFRUbhz5w5u3Lhh8RhXe/nll/HDDz9g27ZtaNSokaHcG9oXEBCAe+65B127dsWcOXPQoUMHfPbZZx7ftoyMDFy+fBldunSBn58f/Pz8sGPHDnz++efw8/Mz1M9T22cqODgY7dq1w+nTpz3+ZwcA0dHRaN26tVFZq1atkJOTA8A7fvcuXLiAX375Bc8//7yhzBva5QgMJE4UEBCALl26IC0tzag8LS0N3bt3d1Gtqi8+Ph5RUVFG7bpz5w527NhhaFeXLl3g7+9vdExeXh6OHTvm8rYLITBx4kSsXbsWW7duRXx8vNHznt4+OUIIlJaWenzb+vbti6NHjyIzM9Pw1rVrV4waNQqZmZlo2rSpR7fPVGlpKU6ePIno6GiP/9kBQI8ePcym2J86dQpNmjQB4B2/e8uWLUNERAQeffRRQ5k3tMshnD2KtqbTT/tdsmSJOHHihHjllVdEcHCwOH/+vKurZlVxcbE4dOiQOHTokAAgPvnkE3Ho0CHDdOX3339fqNVqsXbtWnH06FExYsQI2SlsjRo1Er/88os4ePCg6NOnj1tMYXvhhReEWq0W27dvN5qmV1JSYjjGk9uXmpoqdu7cKbKzs8WRI0fEjBkzhI+Pj9iyZYsQwrPbJkc6y0YIz27fq6++KrZv3y7OnTsn9u7dKwYNGiTq1KljuF54ctuE0E3V9vPzE++++644ffq0WLlypahdu7ZYsWKF4RhPbmN5ebmIjY0V06ZNM3vOk9vlKAwkLvDFF1+IJk2aiICAANG5c2fD9FJ3tm3bNgHA7G3MmDFCCN30vJkzZ4qoqCgRGBgoHnzwQXH06FGjc9y6dUtMnDhR1K9fX9SqVUsMGjRI5OTkuKA1xuTaBUAsW7bMcIwnt2/s2LGG11uDBg1E3759DWFECM9umxzTQOLJ7dOvTeHv7y9iYmLE448/Lo4fP2543pPbprdhwwbRtm1bERgYKFq2bCn+8Y9/GD3vyW3cvHmzACCysrLMnvPkdjmKSgghXNI1Q0RERHQXx5AQERGRyzGQEBERkcsxkBAREZHLMZAQERGRyzGQEBERkcsxkBAREZHLMZAQERGRyzGQEBERkcsxkBCRzWbNmoWOHTu6uhpuZcmSJUhKSrLp2Pnz52Pw4MEOrhGRZ+JKrUQEwHwrdFNjxozB/PnzUVpairCwMCfVytysWbOwfv16ZGZmuqwOeqWlpWjatClWrVqFXr162XR8XFwcvv/+e/Ts2dMJNSTyHH6urgARuYe8vDzDx9999x3+93//12gn1lq1aiEkJAQhISGuqJ5bWrNmDUJCQmwKIwAQGBiIkSNHYt68eQwkRCZ4y4aIAABRUVGGN7VaDZVKZVZmessmOTkZQ4cOxXvvvYfIyEjUrVsXs2fPRllZGV577TXUr18fjRo1wtKlS42+1u+//45hw4ahXr16CAsLw5AhQ3D+/HnD89u3b0e3bt0QHByMunXrokePHrhw4QKWL1+O2bNn4/Dhw1CpVFCpVFi+fDkAoLCwEOPHj0dERARCQ0PRp08fHD582HBOfd0XLlyIxo0bo3bt2njyySdRUFBQ6de1ZNWqVWa3YCo7x+DBg7F+/XrcunVLwU+HyPsxkBBRtWzduhWXLl3Czp078cknn2DWrFkYNGgQ6tWrh3379iElJQUpKSm4ePEiAKCkpASJiYkICQnBzp07sXv3boSEhODhhx/GnTt3UFZWhqFDh6J37944cuQI9uzZg/Hjx0OlUmHYsGF49dVX0aZNG+Tl5SEvLw/Dhg2DEAKPPvoo8vPzsXHjRmRkZKBz587o27cvrl+/bqjrmTNnsHr1amzYsAGbNm1CZmYmXnrpJQCw+nUt2bVrF7p27Wp4bMs5unbtCo1Gg/3799v7R0Hk2Vy61zARuaVly5YJtVptVj5z5kzRoUMHw+MxY8aIJk2aiPLyckNZixYtRK9evQyPy8rKRHBwsPj222+FEEIsWbJEtGjRQmi1WsMxpaWlolatWmLz5s3i2rVrAoDYvn27bN1M6yCEEP/5z39EaGiouH37tlF5s2bNxMKFCw2f5+vrKy5evGh4/ueffxY+Pj4iLy+v0q9r6saNGwKA2Llzp6HM1nPUq1dPLF++3KavQ1RTsIeEiKqlTZs28PGpuJRERkaiXbt2hse+vr4ICwvD5cuXAQAZGRk4c+YM6tSpYxiTUr9+fdy+fRtnz55F/fr1kZycjAEDBuCxxx7DZ599ZjS+RU5GRgb+/PNPhIWFGc4ZEhKC7OxsnD171nBcbGwsGjVqZHickJAArVaLrKwsxV9Xf8slKCjIUGbrOWrVqoWSkhKrbSKqaRhIiKha/P39jR6rVCrZMq1WCwDQarXo0qULMjMzjd5OnTqFkSNHAgCWLVuGPXv2oHv37vjuu+9w7733Yu/evRbroNVqER0dbXbOrKwsvPbaaxY/T38rRf9eydcNCwuDSqXCjRs3jMptOcf169fRoEEDi/UiqokYSIjIqTp37ozTp08jIiIC99xzj9GbWq02HNepUyekpqYiPT0dbdu2xb/+9S8AQEBAAMrLy83OmZ+fDz8/P7NzhoeHG47LycnBpUuXDI/37NkDHx8f3HvvvZV+XVMBAQFo3bo1Tpw4YfactXOcPXsWt2/fRqdOnRR+54i8GwMJETnVqFGjEB4ejiFDhmDXrl3Izs7Gjh07MHnyZOTm5iI7OxupqanYs2cPLly4gC1btuDUqVNo1aoVACAuLg7Z2dnIzMzE1atXUVpain79+iEhIQFDhw7F5s2bcf78eaSnp+PNN9/EgQMHDF87KCgIY8aMweHDh7Fr1y5MmjQJTz31FKKioir9unIGDBiA3bt3Gx7bco5du3ahadOmaNasmQO+u0Sei+uQEJFT1a5dGzt37sS0adPw+OOPo7i4GA0bNkTfvn0RGhqKW7du4bfffsPXX3+Na9euITo6GhMnTsSECRMAAH/961+xdu1aJCYmoqCgAMuWLUNycjI2btyIN954A2PHjsWVK1cQFRWFBx98EJGRkYavfc899+Dxxx/HwIEDcf36dQwcOBALFiww1Mva15Uzbtw4dO7cGYWFhVCr1Tad49tvv8W4ceMc9N0l8lxcqZWIagRHrfD61FNPGW7RVObYsWPo27cvTp06ZXR7ioh4y4aIqFr+/ve/27x67aVLl/DNN98wjBDJ4C0bIqJqaNKkCV5++WWbjrV1Ez6imoi3bIiIiMjleMuGiIiIXI6BhIiIiFyOgYSIiIhcjoGEiIiIXI6BhIiIiFyOgYSIiIhcjoGEiIiIXI6BhIiIiFzu/wGmSsO1YpNcYgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reference path vs Tracked path\n",
    "matched_path, matched_indicies = plot_ref_vs_tracked_path(ref_path=ref_path,\n",
    "                                        tracked_path=tracked_path, \n",
    "                                        obstacle_arr=OBSTACLE_CIRCLES,\n",
    "                                        save_plot=True)\n",
    "\n",
    "# Compute RMSE errors\n",
    "compute_erros(ref_path=ref_path, matched_path=matched_path)\n",
    "\n",
    "# Average linear and angular velocities and their plots\n",
    "results_inputs(u_optims=vehicle.u_history, matched_indices=matched_indicies, step_val=actual_steps)\n",
    "\n",
    "# Computation steps\n",
    "print(f\"Actual number of steps: {actual_steps} and total simulation time: {actual_steps*delta_t:.2f} seconds\")\n",
    "print(f\"Average time per step: {np.mean(time_per_step):0.3f} seconds\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ee7500_proj",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}