| --- |
| license: apache-2.0 |
| tags: |
| - reinforcement-learning |
| - robotics |
| - legged-locomotion |
| - quadruped |
| - mujoco |
| - mjlab |
| - rsl-rl |
| - ppo |
| - onnx |
| pipeline_tag: reinforcement-learning |
| --- |
| |
| # XGO — Luwu Dynamics Quadruped Locomotion Policies |
|
|
| PPO locomotion policies for the Luwu Dynamics (陆吾智能, [xgorobot.com](https://www.xgorobot.com/)) quadruped robots **Mini2S**, **Mini2SW** (wheeled variant), and **Lite3**, trained with [RSL-RL](https://github.com/leggedrobotics/rsl_rl) in [mjlab](https://github.com/mujocolab/mjlab) (Isaac-Lab-style APIs on GPU-accelerated MuJoCo Warp) via the [luwu_mjlab](https://github.com/LuwuDynamics/luwu_mjlab) training environment. |
|
|
| ## Policies |
|
|
| | Folder | Task ID | Robot | Behavior | Iterations | Final mean reward | |
| |---|---|---|---|---|---| |
| | `mini2s_walk/` | `Mini2S-Walk-Flat` | Mini2S | Flat-terrain velocity-tracking walk | 1500 | 87.1 | |
| | `mini2s_turn/` | `Mini2S-Turn-Flat` | Mini2S | Fall recovery / turn-over | 1500 | 112.9 | |
| | `mini2sw_walk/` | `Mini2SW-Walk-Flat` | Mini2SW (wheeled) | Flat-terrain velocity-tracking walk | 1500 | 89.4 | |
| | `mini2sw_turn/` | `Mini2SW-Turn-Flat` | Mini2SW (wheeled) | Fall recovery / turn-over | 1500 | 97.6 | |
| | `lite3_walk/` | `Lite3-Walk-Flat` | Lite3 | Flat-terrain velocity-tracking walk | 1500 | 69.3 | |
|
|
| Each folder contains: |
| - `policy.onnx` — exported inference-only policy (observation → action), robot- and deployment-framework agnostic. |
| - `model_1499.pt` — final RSL-RL PPO checkpoint (actor-critic weights + optimizer state), for resuming training or loading in `luwu_mjlab`/`rsl_rl`. |
| - `params/env.yaml`, `params/agent.yaml` — the exact environment and PPO hyperparameters used for that run. |
|
|
| ## Training setup |
|
|
| - Trained on a single NVIDIA GPU, 4096 parallel environments, 1500 PPO iterations per policy. |
| - Simulator: MuJoCo 3.6.0 / mujoco-warp 3.6.0 (GPU-accelerated). |
| - Framework: [mjlab](https://github.com/mujocolab/mjlab) v1.2.0 + [rsl-rl-lib](https://github.com/leggedrobotics/rsl_rl) 5.0.1. |
| - Task source: [luwu_mjlab](https://github.com/LuwuDynamics/luwu_mjlab) `src/tasks/velocity/`. |
|
|
| ## Usage |
|
|
| With `luwu_mjlab` installed, evaluate a checkpoint: |
|
|
| ```bash |
| python scripts/play.py Mini2S-Walk-Flat \ |
| --checkpoint-file /path/to/mini2s_walk/model_1499.pt |
| ``` |
|
|
| Or run the exported ONNX policy directly with `onnxruntime` for deployment (input/output tensor names and shapes are defined by `luwu_mjlab`'s observation/action manager for each task — see `params/env.yaml` in the matching folder). |
|
|
| ## Disclaimer |
|
|
| These policies were trained in simulation only and have not been validated on hardware. Evaluate carefully (and add safety measures) before any real-robot deployment. |
|
|
