GoalEnv for Robot-Supervisor scheme

[KelvinYang0320]

I integrate GoalEnv from gym/core.py with deepbots for Robot-Supervisor scheme.
GoalEnv also inherite Env, but it imposes a required structure on the observation_space.

1. reset(self):
   self.observation_space must be a Goal-compatible observation space.
   It is required to contain at least three elements, namely observation, desired_goal, and achieved_goal.
   Refer to robot_env.py in gym.

2. compute_reward(self, achieved_goal, desired_goal, info):
   Since in our panda example, we need to get the observation to compute achieved_goal, and then we can compute the reward by using achieved_goal and desired_goal.
   Our original get_reward(action) is actually not that suitable for robotics control task.
   So I think we can let users implement their own step(), so I add raise NotImplementedError in step() function of RobotGoalSupervisor.

I think my coding style or implementation is not good enough.
Any suggestions would be appreciated! 😄

[tsampazk]

Thanks @KelvinYang0320 ! I'll review this PR in the following days.

[KelvinYang0320]

@tsampazk Thank you!
Since it is mainly used for robotic control task in gym, I think I can make an deepworlds example with panda for GoalEnv demo.

[tsampazk]

@tsampazk Thank you! Since it is mainly used for robotic control task in gym, I think I can make an deepworlds example with panda for GoalEnv demo.

That sounds nice so we can actually have a usage example to make it more clear.

[tsampazk]

Left some inline comments, several minor PEP8 comments that should had failed the automated tests (something we should look into) and two major comments about code/class hierarchy structure, that need further discussion.

As a general comment, i think we should also look into how the new GoalEnv classes interact with the emitter/receiver classes. Right now emitter/receiver classes seem to not have access to the GoalEnv stuff.

[KelvinYang0320]

As a general comment, i think we should also look into how the new GoalEnv classes interact with the emitter/receiver classes. Right now emitter/receiver classes seem to not have access to the GoalEnv stuff.

Yes, I am still trying to integrate GoalEnv with emitter/receiver.
However, we might need to decide how to design the highest level class to support both gym.GoalEnv and gym.Env first, and then we can think about how to design emitter-receiver and robot-supervisor.

Thank you for reviewing the code!

[KelvinYang0320]

@tsampazk I have made an example in deepworlds to demo GoalEnv with Panda.
Check this PR.
Also, I have updated this GoalEnv PR for those we have discussed about.
Thank you!