LimX Oli RL Policies

LimX Oli humanoid

Reinforcement-learning policies in ONNX for the LimX Oli full-size humanoid (HU_D04_01, 31 joints), ready to run in MuJoCo or on the real robot with humanoid-rl-deploy-python.

These files are mirrored as-is from humanoid-rl-deploy-python. The GitHub repository is the source of truth.

What's included

Controller Remote buttons Files
Walk R1 + X walk_controller/policy/default/policy.onnx, walk_controller/walk_param.yaml
Mimic (greeting motion) L1 + B mimic_controller/policy/default/policy.onnx, lin_encoder.onnx, priv_encoder.onnx, mimic_controller/mimic_param.yaml
Stand L1 + Y stand_controller/joint_params.yaml
Damping L1 + A damping_controller/joint_params.yaml

HU_D04_01/controllers.yaml lists the controllers loaded by the deploy code.

Quick start (simulation)

Run on Linux x86_64 with humanoid-mujoco-sim and humanoid-rl-deploy-python in the same folder. The deploy repository already contains these policies.

pip install humanoid-mujoco-sim/limxsdk-lowlevel/python3/amd64/limxsdk-*.whl click
export ROBOT_TYPE=HU_D04_01
python humanoid-mujoco-sim/simulator.py            # terminal 1
python humanoid-rl-deploy-python/main.py           # terminal 2
humanoid-mujoco-sim/robot-joystick/robot-joystick  # terminal 3

To download the policies from here instead:

hf download limxdynamics/oli-rl-policies --local-dir ./oli-rl-policies

To deploy your own walking policy, replace walk_controller/policy/default/policy.onnx. See the deploy repository for details.

Safety

These policies drive a physical robot. Test in simulation first, run with a trained operator present, and keep the emergency stop within reach.

Related

License

Apache 2.0, the same as humanoid-rl-deploy-python.

Contact

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