One of the benefits of the modular architecture of robo-gym is that it is fairly simple to add new environments to it.
All the environments are stored under the envs directory, in here we organized the different environments in different folders for each robot.
All the environments are based on the gym.env class, you can base your environment class directly on gym.env or start from one of the classes already included in robo-gym and expand them.
Let's take as an example the UR 10 environments, UR10Env is the base class used for all the environments that use the UR 10 robot, EndEffectorPositioningUR10 inherits from UR10Env and replaces the reward() method to model a task to teach the robot to reach and End Effector Pose. Each environment will have a python class associated to it.
Once you created the class for your environment it has to be added to the registration in order to make it available. Following what it has already been done for the existing environments, add the import of your classes to robo_gym/envs/__init__.py and the registration of the environment to robo_gym/__init__.py.
Integrating new robots and sensors is possible but requires knowledge of ROS and Gazebo, if you are interested in that we would be happy to support you with that, please reach out!