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wertyuilife
2026-03-23 11:13:27 +08:00
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README.md
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Train Unitree Go2 with MoE-CTS. Train Unitree Go2 with MoE-CTS.
This is a reproduction version of [go2_rl_gym](https://github.com/wty-yy/go2_rl_gym) on robotlab/isaaclab. This is a reproduction version of [go2_rl_gym](https://github.com/wty-yy/go2_rl_gym) on RobotLab/IsaacLab.
## Installation Guide ## Installation Guide
### 1. Base Installation ### 1. Install IsaacLab
Install Isaac Lab by following the [installation guide](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html). Install Isaac Lab by following the [installation guide](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html).
Notice that we use certain version of IsaacLab packages, make sure: Notice that we use certain version of IsaacLab packages, make sure:
@@ -18,8 +18,8 @@ isaaclab <= 0.53.1 # tested on 0.53.1
isaaclab-rl <= 0.4.7 # tested on 0.4.7 isaaclab-rl <= 0.4.7 # tested on 0.4.7
``` ```
### 2. Modified Library Setup ### 2. Install customized RSL-RL and RobotLab
This branch uses a customized version of `rsl_rl` and `robot_lab`. To install it, run the following commands in your terminal: We uses a customized version of `rsl_rl` and `robot_lab`. To install it, run the following commands:
```bash ```bash
python -m pip install -e source/robot_lab python -m pip install -e source/robot_lab
@@ -28,14 +28,31 @@ python -m pip install -e source/rsl_rl
## Try examples ## Try examples
You can use the following commands to run all environments: Use the following commands to train and play:
RSL-RL:
```bash ```bash
# Train # Train
python scripts/reinforcement_learning/rsl_rl/train.py --task=<ENV_NAME> --headless python scripts/reinforcement_learning/rsl_rl/train.py --task=Robotlab-Go2-v0 --headless --num_envs=4096
# Play # Play
python scripts/reinforcement_learning/rsl_rl/play.py --task=<ENV_NAME> python scripts/reinforcement_learning/rsl_rl/play.py --task=Robotlab-Go2-v0 --num_envs=1024
``` ```
## Configuration
1. Modify `source/robot_lab/robot_lab/tasks/go2/env_cfg.py` for environment config.
2. Modify `source/robot_lab/robot_lab/tasks/go2/rsl_rl_cfg.py` for algorithm config.
3. Modify `source/robot_lab/robot_lab/tasks/go2/__init__.py` to add your own task with new config.
## Acknowledgements
This repository would not exist without the following open-source projects:
- [isaac_lab](https://github.com/isaac-sim/IsaacLab): Unified framework for robot learning built on NVIDIA Isaac Sim.
- [rsl_rl](https://github.com/leggedrobotics/rsl_rl.git): Reinforcement learning algorithms.
- [robot_lab](https://github.com/fan-ziqi/robot_lab.git): RL Extension Library for Robots, Based on IsaacLab.
Related publications implemented in this repo:
- [CTS: Concurrent Teacher-Student Reinforcement Learning for Legged Locomotion](https://arxiv.org/pdf/2405.10830)

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source/robot_lab/robot_lab/tasks/go2/__init__.py
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@@ -23,7 +23,6 @@ gym.register(
disable_env_checker=True, disable_env_checker=True,
kwargs={ kwargs={
"env_cfg_entry_point": f"{__name__}.env_cfg:Go2EnvCfg", "env_cfg_entry_point": f"{__name__}.env_cfg:Go2EnvCfg",
# "env_cfg_entry_point": f"{__name__}.origin_env_cfg:UnitreeGo2RoughEnvCfg",
"rsl_rl_cfg_entry_point": f"{__name__}.rsl_rl_cfg:MoECTSRunnerCfg", "rsl_rl_cfg_entry_point": f"{__name__}.rsl_rl_cfg:MoECTSRunnerCfg",
}, },
) )