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go2_walk

Go2 Walking Demo

Demonstration Code for Unitree Go2 Quadruped Robot Walking

dreamwaq (Main) • gym_basic • unitree_rl_gym • wtw

Project Structure

go2_walk/
├── dreamwaq/           # [Main] Rough terrain with state estimation
│   ├── legged_gym/
│   └── rsl_rl/
├── gym_basic/          # [Sub] Basic IsaacGym examples
├── unitree_rl_gym/     # [Ref] Flat terrain locomotion
└── wtw/                # [Ref] Sim-to-Real deployment
    ├── go2_gym/
    ├── go2_gym_learn/
    └── go2_gym_deploy/

⭐ dreamwaq (Main)

Rough Terrain Locomotion with State Estimation

License: MIT
Author Jungyeon Lee (curieuxjy)
Paper DreamWaQ: Learning Robust Quadrupedal Locomotion
Achievement 1st Place at ICRA 2023 Autonomous Quadruped Robot Challenge (QRC) Final
Related Fall Recovery Task
Training Log WandB Dashboard

I independently implemented the DreamWaQ algorithm based on the paper. The core component, Context-aided Estimator Network (CENet), has been carefully implemented and verified to work as described. Feel free to explore the code and experiment with it!

📖 For detailed setup instructions including Docker configuration and training commands, please refer to the dreamwaq/README.md.

📦 gym_basic

Go2 in IsaacGym

  • IsaacGym ver.4 basic examples
  • Camera and joint inspection demos

📚 unitree_rl_gym

Flat Terrain Locomotion (Reference)
Original unitreerobotics/unitree_rl_gym
Based on leggedrobotics/legged_gym

📚 wtw

Sim-to-Real Deployment (Reference)
Paper Walk These Ways
Original Teddy-Liao/walk-these-ways-go2
Based on Improbable-AI/walk-these-ways

References