# GR00T-WholeBodyControl: Whole-Body Control for Humanoid Loco-Manipulation
**Source:** [GitHub — NVlabs/GR00T-WholeBodyControl](https://github.com/NVlabs/GR00T-WholeBodyControl)
**Authors:** NVIDIA Labs (NVlabs)
**Fetched:** 2026-02-13
**Type:** Technical Software / Open-Source Project (not a traditional research paper)

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## Overview

GR00T-WholeBodyControl is a software stack developed by NVIDIA Labs for loco-manipulation experiments across multiple humanoid platforms, with primary support for the Unitree G1. The repository provides three core components: whole-body control policies, a teleoperation stack, and a data exporter.

This is not a standalone research paper but rather an open-source project that forms the low-level motor control layer of the broader NVIDIA Isaac GR00T ecosystem. It serves as the foundational whole-body controller underneath the GR00T N1.6 vision-language-action (VLA) policy.

## Architecture and Methods

- **Training Framework:** Whole-body reinforcement learning trained in NVIDIA Isaac Lab and Isaac Sim
- **Motion Generation:** Produces human-like, dynamically stable motion primitives covering locomotion, manipulation, and coordinated multi-contact behaviors
- **Policy Architecture:** Uses a 32-layer diffusion transformer that generates state-relative action predictions for smoother, less jittery movements
- **Transfer Method:** Policies trained in simulation are transferred zero-shot to physical humanoids, minimizing task-specific fine-tuning

## Key Capabilities

- Whole-body control policies for coordinated locomotion and manipulation
- Teleoperation stack with support for Meta Pico controllers, LeapMotion, and HTC Vive with Joy-Con controllers
- Integrated data exporter for trajectory recording and task-prompt-based data annotation
- Simulation support via RoboCSA environment
- Real robot deployment with proper network configuration
- Docker containerization with GPU support via NVIDIA Container Toolkit

## Technical Details

- **Language Composition:** Python (84.9%), C++ (6.7%), C (6.1%), Shell (1.7%)
- **System Requirements:** Ubuntu 22.04, NVIDIA GPU, Docker with NVIDIA Container Toolkit
- **Supported Robots:** Unitree G1 (primary), GR-1 humanoids, mobile manipulators, bimanual arms

## G1 Relevance

GR00T-WholeBodyControl has **primary support for the Unitree G1** — the G1 is the main development platform. The loco-manipulation task is built on MuJoCo using the Unitree G1, requiring the robot to navigate, pick up objects, and place them at target locations while maintaining balance and whole-body coordination. This represents one of the most complete open-source whole-body control stacks available for the G1 platform.

## References

- GitHub Repository: https://github.com/NVlabs/GR00T-WholeBodyControl
- Isaac GR00T Integration: https://github.com/NVIDIA/Isaac-GR00T/blob/main/examples/GR00T-WholeBodyControl/README.md
- NVIDIA Technical Blog: https://developer.nvidia.com/blog/building-generalist-humanoid-capabilities-with-nvidia-isaac-gr00t-n1-6-using-a-sim-to-real-workflow/