{"id":30749750,"url":"https://github.com/hybridrobotics/whole_body_tracking","last_synced_at":"2025-09-04T06:46:07.752Z","repository":{"id":309848158,"uuid":"1036109133","full_name":"HybridRobotics/whole_body_tracking","owner":"HybridRobotics","description":null,"archived":false,"fork":false,"pushed_at":"2025-08-24T17:46:54.000Z","size":215,"stargazers_count":576,"open_issues_count":1,"forks_count":48,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-08-24T21:58:52.415Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/HybridRobotics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-08-11T15:12:45.000Z","updated_at":"2025-08-24T17:46:57.000Z","dependencies_parsed_at":"2025-08-14T06:18:35.764Z","dependency_job_id":"0454a3f6-eeb4-47b3-9c8e-4afe01a19990","html_url":"https://github.com/HybridRobotics/whole_body_tracking","commit_stats":null,"previous_names":["hybridrobotics/whole_body_tracking"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/HybridRobotics/whole_body_tracking","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HybridRobotics%2Fwhole_body_tracking","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HybridRobotics%2Fwhole_body_tracking/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HybridRobotics%2Fwhole_body_tracking/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HybridRobotics%2Fwhole_body_tracking/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/HybridRobotics","download_url":"https://codeload.github.com/HybridRobotics/whole_body_tracking/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HybridRobotics%2Fwhole_body_tracking/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273567586,"owners_count":25128631,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-04T02:00:08.968Z","response_time":61,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-09-04T06:46:02.270Z","updated_at":"2025-09-04T06:46:07.738Z","avatar_url":"https://github.com/HybridRobotics.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# BeyondMimic Motion Trakcing Code\n\n[![IsaacSim](https://img.shields.io/badge/IsaacSim-4.5.0-silver.svg)](https://docs.omniverse.nvidia.com/isaacsim/latest/overview.html)\n[![Isaac Lab](https://img.shields.io/badge/IsaacLab-2.1.0-silver)](https://isaac-sim.github.io/IsaacLab)\n[![Python](https://img.shields.io/badge/python-3.10-blue.svg)](https://docs.python.org/3/whatsnew/3.10.html)\n[![Linux platform](https://img.shields.io/badge/platform-linux--64-orange.svg)](https://releases.ubuntu.com/20.04/)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\u0026logoColor=white)](https://pre-commit.com/)\n[![License](https://img.shields.io/badge/license-MIT-yellow.svg)](https://opensource.org/license/mit)\n\n[[Website]](https://beyondmimic.github.io/)\n[[Arxiv]](https://arxiv.org/abs/2508.08241)\n[[Video]](https://youtu.be/RS_MtKVIAzY)\n\n## Overview\n\nBeyondMimic is a versatile humanoid control framework that provides highly dynamic motion tracking with the\nstate-of-the-art motion quality on real-world deployment and steerable test-time control with guided diffusion-based\ncontrollers.\n\nThis repo covers the motion tracking training in BeyondMimic. **You should be able to\ntrain any sim-to-real-ready motion in the LAFAN1 dataset, without tuning any parameters**.\n\nFor sim-to-sim and sim-to-real deployment, please refer to\nthe [motion_tracking_controller](https://github.com/HybridRobotics/motion_tracking_controller).\n\n## Installation\n\n- Install Isaac Lab v2.1.0 by following\n  the [installation guide](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html). We recommend\n  using the conda installation as it simplifies calling Python scripts from the terminal.\n\n- Clone this repository separately from the Isaac Lab installation (i.e., outside the `IsaacLab` directory):\n\n```bash\n# Option 1: SSH\ngit clone git@github.com:HybridRobotics/whole_body_tracking.git\n\n# Option 2: HTTPS\ngit clone https://github.com/HybridRobotics/whole_body_tracking.git\n```\n\n- Pull the robot description files from GCS\n\n```bash\n# Enter the repository\ncd whole_body_tracking\n# Rename all occurrences of whole_body_tracking (in files/directories) to your_fancy_extension_name\ncurl -L -o unitree_description.tar.gz https://storage.googleapis.com/qiayuanl_robot_descriptions/unitree_description.tar.gz \u0026\u0026 \\\ntar -xzf unitree_description.tar.gz -C source/whole_body_tracking/whole_body_tracking/assets/ \u0026\u0026 \\\nrm unitree_description.tar.gz\n```\n\n- Using a Python interpreter that has Isaac Lab installed, install the library\n\n```bash\npython -m pip install -e source/whole_body_tracking\n```\n\n## Motion Tracking\n\n### Motion Preprocessing \u0026 Registry Setup\n\nIn order to manage the large set of motions we used in this work, we leverage the WandB registry to store and load\nreference motions automatically.\nNote: The reference motion should be retargeted and use generalized coordinates only.\n\n- Gather the reference motion datasets (please follow the original licenses), we use the same convention as .csv of\n  Unitree's dataset\n\n    - Unitree-retargeted LAFAN1 Dataset is available\n      on [HuggingFace](https://huggingface.co/datasets/lvhaidong/LAFAN1_Retargeting_Dataset)\n    - Sidekicks are from [KungfuBot](https://kungfu-bot.github.io/)\n    - Christiano Ronaldo celebration is from [ASAP](https://github.com/LeCAR-Lab/ASAP).\n    - Balance motions are from [HuB](https://hub-robot.github.io/)\n\n\n- Log in to your WandB account; access Registry under Core on the left. Create a new registry collection with the name \"\n  Motions\" and artifact type \"All Types\".\n\n\n- Convert retargeted motions to include the maximum coordinates information (body pose, body velocity, and body\n  acceleration) via forward kinematics,\n\n```bash\npython scripts/csv_to_npz.py --input_file {motion_name}.csv --input_fps 30 --output_name {motion_name} --headless\n```\n\nThis will automatically upload the processed motion file to the WandB registry with output name {motion_name}.\n\n- Test if the WandB registry works properly by replaying the motion in Isaac Sim:\n\n```bash\npython scripts/replay_npz.py --registry_name={your-organization}-org/wandb-registry-motions/{motion_name}\n```\n\n- Debugging\n    - Make sure to export WANDB_ENTITY to your organization name, not your personal username.\n    - If /tmp folder is not accessible, modify csv_to_npz.py L319 \u0026 L326 to a temporary folder of your choice.\n\n### Policy Training\n\n- Train policy by the following command:\n\n```bash\npython scripts/rsl_rl/train.py --task=Tracking-Flat-G1-v0 \\\n--registry_name {your-organization}-org/wandb-registry-motions/{motion_name} \\\n--headless --logger wandb --log_project_name {project_name} --run_name {run_name}\n```\n\n### Policy Evaluation\n\n- Play the trained policy by the following command:\n\n```bash\npython scripts/rsl_rl/play.py --task=Tracking-Flat-G1-v0 --num_envs=2 --wandb_path={wandb-run-path}\n```\n\nThe WandB run path can be located in the run overview. It follows the format {your_organization}/{project_name}/ along\nwith a unique 8-character identifier. Note that run_name is different from run_path.\n\n## Code Structure\n\nBelow is an overview of the code structure for this repository:\n\n- **`source/whole_body_tracking/whole_body_tracking/tasks/tracking/mdp`**\n  This directory contains the atomic functions to define the MDP for BeyondMimic. Below is a breakdown of the functions:\n\n    - **`commands.py`**\n      Command library to compute relevant variables from the reference motion, current robot state, and error\n      computations. This includes pose and velocity error calculation, initial state randomization, and adaptive\n      sampling.\n\n    - **`rewards.py`**\n      Implements the DeepMimic reward functions and smoothing terms.\n\n    - **`events.py`**\n      Implements domain randomization terms.\n\n    - **`observations.py`**\n      Implements observation terms for motion tracking and data collection.\n\n    - **`terminations.py`**\n      Implements early terminations and timeouts.\n\n- **`source/whole_body_tracking/whole_body_tracking/tasks/tracking/tracking_env_cfg.py`**\n  Contains the environment (MDP) hyperparameters configuration for the tracking task.\n\n- **`source/whole_body_tracking/whole_body_tracking/tasks/tracking/config/g1/agents/rsl_rl_ppo_cfg.py`**\n  Contains the PPO hyperparameters for the tracking task.\n\n- **`source/whole_body_tracking/whole_body_tracking/robots`**\n  Contains robot-specific settings, including armature parameters, joint stiffness/damping calculation, and action scale\n  calculation.\n\n- **`scripts`**\n  Includes utility scripts for preprocessing motion data, training policies, and evaluating trained policies.\n\nThis structure is designed to ensure modularity and ease of navigation for developers expanding the project.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhybridrobotics%2Fwhole_body_tracking","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhybridrobotics%2Fwhole_body_tracking","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhybridrobotics%2Fwhole_body_tracking/lists"}