HY-Embodied-0.5-X: An Enhanced Embodied Foundation Model for Real-World Agents

End-to-end pipeline converting generative videos (Veo, Sora) to humanoid robot motions

🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

Projects from basic algorithms to MARL. Implements MADDPG,MATD3,MA/HAPPO in Predator-Prey pursuit games with PettingZoo MPE environments.

这是我的强化学习笔记

PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译，支持 Google/DeepL/Ollama/OpenAI 等服务，提供 CLI/GUI/Docker

这是我的深度强化学习的学习笔记与总结

Dexterous Grasping Policy from Point Clouds

[RSS 2023] Diffusion Policy Visuomotor Policy Learning via Action Diffusion

[RSS 2024] 3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations

Research on Coding Agents

The repo is finally unlocked. enjoy the party! The fastest repo in history to surpass 100K stars ⭐. Join Discord: https://discord.gg/5TUQKqFWd Built in Rust using oh-my-codex.

GentleHumanoid: Whole body Motion Tracking with Compliance - Inference and Deploy

GentleHumanoid: Whole Body Motion Tracking with Compliance - Training

仅需Python基础，从0构建自己的具身智能机器人；从0逐步构建VLA/OpenVLA/SmolVLA/Pi0， 深入理解具身智能

[CVPR 2025 Highlight] InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions

🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.

A lightweight suite of motion imitation methods for training controllers.

基于mujoco仿真环境对unitree g1机器操作的研究和学习

This is a mostly identical fork of carlosferrazza/humanoid-bench for demo purposes for my friend moses

A curated list of state-of-the-art research in embodied AI, focusing on vision-language-action (VLA) models, vision-language navigation (VLN), and related multimodal learning approaches.

[RSS 2025] Learning to Act Anywhere with Task-centric Latent Actions

A simulation environment and benchmark for human-to-robot object handovers

Official code for CVPR'23 paper: Learning Human-to-Robot Handovers from Point Clouds

Updated the software dependencies to make this project runnable on a modern Ubuntu 22.04, Python 3.10, Cuda 12.x setup