Course instructor : Prof. Tapaskumar Maiti
- Jigar Shekhat - 202211004
- Man Desai - 202211040
- Vatsal Shingala - 202211073
A rough outline for the repository that might be useful for adding your own robot:
LearningHumanoidWalking/
├── envs/ <-- Actions and observation space, PD gains, simulation step, control decimation, init, ...
├── tasks/ <-- Reward function, termination conditions, and more...
├── rl/ <-- Code for PPO, actor/critic networks, observation normalization process...
├── models/ <-- MuJoCo model files: XMLs/meshes/textures
├── trained/ <-- Contains pretrained model for JVRC
└── scripts/ <-- Utility scripts, etc.
- Python version: 3.7.11
- Pytorch
- pip install:
- mujoco==2.2.0
- mujoco-python-viewer
- ray==1.9.2
- transforms3d
- matplotlib
- scipy
Environment names supported:
| Task Description | Environment name |
|---|---|
| Basic Walking Task | 'jvrc_walk' |
| Stepping Task (using footsteps) | 'jvrc_step' |
$ python run_experiment.py train --logdir <path_to_exp_dir> --num_procs <num_of_cpu_procs> --env <name_of_environment>
We need to write a script specific to each environment.
For example, debug_stepper.py can be used with the jvrc_step environment.
$ PYTHONPATH=.:$PYTHONPATH python scripts/debug_stepper.py --path <path_to_exp_dir>
Ascending stairs:
Descending stairs:
Walking on curves:
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