Skip to content

Releases: NVlabs/HOVER

Unitree H1 Deployment Release

14 Mar 21:41
@steple steple
deployment-release
54b1098
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.
Compare
Choose a tag to compare
Unitree H1 Deployment Release Latest
Latest

Release Notes

Added

  • Hardware support for Unitree H1 robot

    • SDK wrapper for robot control
    • Hardware configuration and safety parameters
    • Test suite for hardware integration

  • Sim-to-real deployment tools

    • Deployment script for running policies on real robot
    • Real robot environment configuration
    • Hardware installation and setup documentation

Modified

  • Enhanced observation handling to support real robot sensors
  • Added hardware dependencies to requirements

These changes enable trained policies to be deployed on physical Unitree H1 robots.

Assets 2
Loading

HOVER WBC Initial Release

12 Mar 20:44
@steple steple
initial-release
eb7bce8
Compare
Choose a tag to compare
HOVER WBC Initial Release

Release Notes

Overview

Initial release of HOVER WBC, a neural whole-body controller framework for humanoid robots implemented as an IsaacLab extension. This release implements the methodologies described in the OmniH2O and HOVER papers.

Key Features

Core Functionality

  • Teacher-student policy training pipeline for humanoid motion control
  • Support for both generalist and specialist policies
  • Comprehensive motion tracking and evaluation metrics
  • Sim-to-sim validation using Mujoco environment

Training Capabilities

  • AMASS dataset integration with retargeting support for Unitree H1 robot
  • Configurable training environments
  • Resumable training from checkpoints
  • Multiple tracking modes including OmniH2O and humanplus

Development Tools

  • Unit testing framework
  • Pre-commit hooks for code quality
  • IDE integration support (VSCode)
  • Docker container support for headless operation

Technical Requirements

  • IsaacSim 4.5.0
  • IsaacLab 2.0.0
  • Python 3.10
  • Ubuntu 22.04

Installation

  • Automated dependency installation via install_deps.sh
  • Environment configuration through YAML files
  • Flexible configuration system with override capabilities

Documentation

  • Comprehensive README with installation and usage instructions
  • Detailed API documentation
  • Example configurations and training scripts

Known Limitations

  • AMASS dataset not included due to licensing restrictions
  • Current implementation includes four pre-selected modes for generalist policies
  • Mujoco wrapper limited to single environment operation

License

Released under Apache License 2.0

Loading