Comments (5)
Hi Suman,
The empty environment is implemented here: https://github.com/maximecb/gym-minigrid/blob/master/gym_minigrid/envs/empty.py
The rest of the logic you are looking for is in minigrid.py: https://github.com/maximecb/gym-minigrid/blob/master/gym_minigrid/minigrid.py
In particular, the process_vis
function computes a visibility mask, the cells that are visible to the agent. It basically propagates visibility forward until a wall or closed door is hit.
For moving obstacles, if you just want one environment, I would suggest overriding the step
function in your new environment class. Keep track of your moving object, and update its position using self.grid.set(i, j, object)
. Since the motion of your obstacle is random, you will likely want to use the self.env._rand_int()
method. This will ensure that you always get the same behavior in your environment given the same seed.
Let me know if you have any other questions.
from minigrid.
Thank you for your perfect guidelines.
I was able to successfully add a new environment with Dynamic Obstacles. This environment will be used for research at TU Darmstadt testing novel RL algorithms for mobile robot navigation with dynamic obstacles. Here is the link to the branch. I have added a short description of the environment in the README under the section of "Dynamic obstacles environment".
It may be useful to merge this branch with the master for future robotics research.
Thank you.
from minigrid.
Well done! I would be happy to merge it if you create a pull request :)
from minigrid.
I will do it soon. I just found a small bug. I'll rectify it and get back to you.
from minigrid.
I have created the pull request :)
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