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GR00T Whole-Body Control is NVIDIA’s unified platform for training, evaluating, and deploying advanced humanoid robot controllers. It includes the decoupled controller used with GR00T N1.5 and N1.6, combining reinforcement learning for the lower body with inverse kinematics for the upper body. The GEAR-SONIC system learns a broad set of natural motor skills from large-scale human motion data through a unified tracking policy. Released Unitree G1 checkpoints support motion references, whole-body teleoperation, planning, and vision-language-action workflows. A C++ and TensorRT inference stack provides real-hardware deployment, while PyTorch checkpoints support Isaac Lab evaluation and continued training. The repository also includes VR teleoperation, data collection, kinematic planning, and low-latency control configurations. MotionBricks adds real-time latent motion generation for interactive animation and robotics applications.
Features
- Decoupled reinforcement learning and IK control
- GEAR-SONIC humanoid foundation controller
- Unitree G1 pretrained checkpoints
- C++ and TensorRT robot deployment
- VR teleoperation and VLA data collection
- MotionBricks real-time motion generation
Project Samples
