Comments (4)
While there are a few different environment classes, they just abstract various features that the codebase uses. The only task this code base implements is multi-arm motion planning, and most of the functionality is in environment/baseEnv.py
from decentralized-multiarm.
While there are a few different environment classes, they just abstract various features that the codebase uses. The only task this code base implements is multi-arm motion planning, and most of the functionality is in
environment/baseEnv.py
Thank you. Should each arm work cooperatively to complete these tasks?
from decentralized-multiarm.
Thank you. Should each arm work cooperatively to complete these tasks?
Yep! You can follow the instructions in the README.md to play around with them.
from decentralized-multiarm.
Thank you. Should each arm work cooperatively to complete these tasks?
Yep! You can follow the instructions in the README.md to play around with them.
Geat, cool, hope it can help my multi-agent RL research.
from decentralized-multiarm.
Related Issues (15)
- About pretrained weights
- wget downloading problem HOT 4
- ERROR worker.py:772 -- Exception raised in creation task: The actor died because of an error raised in its creation task, ray::TaskLoader.__init__() HOT 2
- Training too slow problem HOT 1
- Questions on Converting .p Files in robot0 Folder and Modifying Task Runners for Custom Tasks
- I would like to know if “” --expert_trajectories“” provides example files. I didn't find in the readme. Thanks!
- Gripper Open/Close HOT 1
- Add a license like apache 2? HOT 1
- Command to run bin placing task? HOT 3
- AttributeError: 'NoneType' object has no attribute 'rsample' HOT 8
- How to continue training after being interrupted? HOT 1
- Under what conditions will the program end training? HOT 1
- A promblem
- Evaluation error, tasks.py", line 342 assert len(self.files) > 0 AssertionError HOT 3
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