ti5robot-23.63

Name: ti5robot-23.63 Version: 1.0.0 Summary: mujoco environments for humanoid robot Author: Huiyang Kong Author-email: k15651356039@163.com License: BSD-3-Clause

Code for the papers:

• Learning Bipedal Walking On Planned Footsteps For Humanoid Robots (Humanoids2022) Rohan P. Singh, Mehdi Benallegue, Mitsuharu Morisawa, Rafael Cisneros, Fumio Kanehiro

• Learning Bipedal Walking for Humanoids with Current Feedback (arxiv) Rohan P. Singh, Zhaoming Xie, Pierre Gergondet, Fumio Kanehiro (WIP on branch topic/omnidirectional-walk)

Code structure:

A rough outline for the repository that might be useful for adding your own robot:

ti5robot-23.63/
├── 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.

Requirements:

• Python version: 3.10.6
• Pytorch
• pip install:
  • mujoco==3.2.6
  • mujoco-python-viewer==0.1.4
  • ray==2.40.0
  • transforms3d==0.4.2
  • matplotlib==3.9.3
  • scipy==1.14.1
  • torch==2.5.1
  • serial==0.0.97
  • dm_control==1.0.31
• pip install mujoco==3.2.6 mujoco_python_viewer==0.1.4 ray==2.40.0 transforms3d==0.4.2 matplotlib==3.9.3 scipy==1.14.1 torch==2.5.1 serial==0.0.97 dm_control==1.0.31

Usage:

Environment names supported:

Task Description	Environment name
Basic Walking Task	'jvrc_walk'
Stepping Task (using footsteps)	'jvrc_step'

To train:

 在pycharm中，配置好run_experiment.py的运行环境train --env jvrc_walk和工作目录，然后运行run_experiment.py

To play:

 在pycharm中，配置好debug_stepper.py的运行环境--path logs_dir和工作目录，然后运行debug_stepper.py

What you should see:

Ascending stairs:

Descending stairs:

Walking on curves: