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This repository provides Unitree G1 deployment code for GRIT v0.0.1, a whole-body motion-tracking control algorithm for humanoid robots.
[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation
First JEPA-based learning framework for mapping-free LiDAR-based perceptive locomotion
Official implementation of Perceptive Behavior Foundation Model
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
This repository contains an implementation for performing 3D animal (quadruped) reconstruction from a monocular image or video. The system adapts the pose (limb positions) and shape (animal type/he…
Code accompanying the paper "Learning Agile Robotic Locomotion Skills by Imitating Animals"
Code from the ECCV 2024 paper "Animal Avatar Reconstructing Animatable 3D Animals from Casual Videos".
An IsaacLab DirectEnv for basic quadrupedal locomotion tasks, with support for multiple quadruped robots, sim-to-sim, and sim-to-real pipelines
Elevation Mapping on GPU.
HoloMotion: A Foundation Model for Whole-Body Humanoid Control
GPU-parallel PPO training for a 3D Unitree H1 penalty kick in NVIDIA Isaac Lab.
Blender extension and standalone script for converting terrain meshes into MuJoCo HField collision assets and MJCF scenes.
RynnVLA-002: A Unified Vision-Language-Action and World Model
RL framework for whole-body legged manipulation across 7 robot platforms
RL Extension Library for Robots, Based on IsaacLab.
Simulation verification and physical deployment of robot reinforcement learning algorithms, suitable for quadruped robots, wheeled robots, and humanoid robots. "sar" represents "simulation and real"
Training Go2W based on the HIMLoco framework
train, export, and deploy HimLoco policies in the Isaac Lab environment
AMP-based quadruped locomotion framework on Isaac Lab
This is the official code repo for DiT4DiT, a Vision-Action-Model (VAM) framework that combines video generation model with flow-matching-based action prediction for generalizable robotic manipulat…
BFM_Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning
A deployment framework for reinforcement learning-based motion control of legged robots, covering bipedal, quadrupedal, wheeled-bipedal, and wheeled-quadrupedal robots.