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LeRobot aims to provide models, datasets, and tools for real-world robotics in PyTorch. The goal is to lower the barrier to entry so that everyone can contribute to and benefit from shared datasets and pretrained models.

This repo is Jumper’s AI toolkit for appearance, motion, and scene creation. Open this repo in an AI coding assistant and try the prompts below.

The world is rushing to build AI systems. It is not engineering them.

[Lumina具身智能社区] 具身智能技术指南 Embodied-AI-Guide

openpi holds open-source models and packages for robotics, published by the Physical Intelligence team.

The scripts load VPP2 directly from this checkout; installing the vpp2 package is unnecessary. txt.

🚀 100% Open Source · Embodied AI · Full Hardware + Software Stack

Simulation platform for general-purpose robotics & embodied AI learning.

RoboICL is an in-context robot-control framework that adapts a frozen general-purpose vision-language model from demonstrations and its own execution history. It requires no robot-specific parameter update and no learned vision-language-action model.

Welcome to GR00T Whole-Body Control (WBC)! This is a unified platform for developing and deploying advanced humanoid controllers. 6 and GEAR-SONIC

OpenWAM is an open research stack for systematically developing World-Action Models (WAMs). It turns tightly coupled design choices into modular components and controlled experiments. It consists of:

A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs. 3, Kimi-K3 and more.

An all-in-one VLA engineering platform for embodied AI — from data to real-robot deployment.

SuperDex brings together a purpose-built physics engine, robotics authoring tools, and a scalable reinforcement learning interface in a unified simulation platform, with VR-based teleoperation and additional capabilities planned for future releases.

Intrinsic Core™ provides an open, local runtime, SDK, and hardware agnostic, real-time control framework for industrial robotics.

0-9B is a multimodal foundation model for general visual understanding, spatial reasoning, agentic tool use, and embodied-AI research. 5-9B language backbone with a C-RADIOv4-H vision encoder, supports text, images and videos with any-resolution visual input.

LightNav-0 is a compact generalist embodied navigation model that elicits the spatial intelligence of a pretrained vision-language model (Qwen3-VL) and aligns it with navigation, without task-specific prediction heads.

Cadence's goal is a continuing learning system with the flexibility of animal and human problem solving: acquiring skills from experience, retaining useful knowledge, imagining alternatives and creating solutions across domains.

A unified framework for training, fine-tuning, and evaluating World Action Models

Without training models, RoboHarness combines visual clicks, keypoint tracking, and geometric constraints to provide an embodied control panel for an LLM agent.

Zetta is an efficient closed-loop embodied harness for self-evolving physical intelligence. It evolves code-based runtime critics and recovery skills online while keeping the base policy frozen. Project Page:

Motus2: A Self-Evolving General World Model for Dexterous Manipulation

WholeBodyVLA is a unified Vision-Language-Action framework for large-space humanoid loco-manipulation.

A learned correspondence is reused by motions with the same source template and target robot.

The in-context human video generation pipeline starts from task-sampled robot trajectories that retain executable actions.

One CLI for all your robots. Connect them, command them, and let them work together, each with an LLM for a brain (Claude, OpenAI, Gemini, Grok, or local via Ollama or vLLM), VLAs for arms and decision LLMs (Jev, Laya, Kev).

Flex-π is a 6B-parameter world-action model for robot manipulation. It jointly predicts future RGB, 3D pointmaps, DINOv3 semantics, and actions in training, then deploys as a VLA, as a full world-action model, or as anything in between — all from a single checkpoint.

Official implementation of StreamPI, built on openpi , with additional, fully validated support for JAX multi-node distributed training beyond the standard single-node setup, enabling substantially more efficient training without compromising model performance .

A high-performance serving framework for robotics models.

Embodied-intelligence simulation backend for multi-agent orchestration and Unreal Engine integration.