Lightweight implementation of Robotic World Model (RWM) and Uncertainty-Aware Robotic World Model (RWM-U)

🔥 [ICLR 2026] Benchmark for robotic tabletop manipulation memory-intensive tasks

BFM_Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning

Judo: a hackable sampling-based MPC toolbox

🔥Benchmarking of Neural Network Architectures in Reinforcement Learning.

[arXiv 2025] VisualMimic: Visual Humanoid Loco-Manipulation via Motion Tracking and Generation

Sim-to-real RL training and deployment tools for the Unitree Go1 robot.

3D CAD Model of a Classic Skatebord and URDF File

Reverse Curriculum RL approach for robodog climbing on a skateboard

Low-level locomotion policy training in Isaac Lab

Whole-Body Model-Predictive Control of Legged Robots with MuJoCo

Minimal, clean, single-file implementations of common robotics controllers in MuJoCo.

Official implementation of OpenWBT.

This repository contains the code base for the paper "Gait in Eight: Efficient On-Robot Learning for Omnidirectional Quadruped Locomotion."

[RSS 2025] "ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills"

GPU-optimized version of the MuJoCo physics simulator, designed for NVIDIA hardware.

ProtoMotions is a GPU-accelerated simulation and learning framework for training physically simulated digital humans and humanoid robots.

This is the official PyTorch implementation of the CVPR'2022 paper "H4D: Human 4D Modeling by Learning Neural Compositional Representation".

Code and weights for the paper "Cluster and Predict Latents Patches for Improved Masked Image Modeling"

HOVER

A suite of image and video neural tokenizers

An open-source library for GPU-accelerated robot learning and sim-to-real transfer.

Lipschitz-constrained Unsupervised Skill Discovery (ICLR 2022)

iQRL: implicitly Quantized Representations for Sample-efficient Reinforcement Learning

Predictable MDP Abstraction for Unsupervised Model-Based RL (ICML 2023)

Pytorch replication of the paper : Robust Predictable Control