A curated list of awesome projects, resources, and research related to Embodied AI and Humanoid Robotics.
- Introduction
- Scene Understanding
- Data Collection
- Action Output
- Open Source Projects
- Datasets
- Companies & Robots
- Research Papers
- Community
Embodied Intelligence refers to AI systems that learn and interact through physical embodiment, often in robotics platforms. This list focuses on projects combining artificial intelligence with physical interaction capabilities.
Description | Paper | Code | |
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SAM | Segmentation | Paper | Code |
YOLO-World | Open-Vocabulary Detection | Paper | Code |
Description | Paper | Code | |
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SAM3D | Segmentation | Paper | Code |
PointMixer | Understanding | Paper | Code |
Description | Paper | Code | |
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GPT4V | MLM(Image+Language->Language) | Paper | |
Claude3-Opus | MLM(Image+Language->Language) | Paper | |
GLaMM | Pixel Grounding | Paper | Code |
All-Seeing | Pixel Grounding | Paper | Code |
LEO | 3D | Paper | Code |
Description | Paper | Code | |
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Vid2Robot | Paper | ||
RT-Trajectory | Paper | ||
MimicPlay | Paper | Code |
Description | Paper | Code | |
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UMI | Two-Fingers | Paper | Code |
DexCap | Five-Fingers | Paper | Code |
HIRO Hand | Hand-over-hand | Paper |
Description | Paper | Code | |
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MimicGen | Paper | Code | |
RoboGen | Paper | Code |
Description | Paper | Code | |
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Diffusion Policy | Paper | Code | |
ACT | Paper | Code |
Description | Paper | Code | |
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CLIPort | Pick&Place | Paper | Code |
Robo-Affordances | Contact&Post-contact trajectories | Paper | Code |
Robo-ABC | Paper | Code | |
Where2Explore | Few shot learning from semantic similarity | Paper | |
Move as You Say | Affordance to motion from diffusion model | Paper | |
AffordanceLLM | Grounding affordance with LLM | Paper | |
Environment-aware Affordance | Paper | ||
OpenAD | Open-Voc Affordance Detection | Paper | Code |
RLAfford | End-to-End affordance learning | Paper | |
General Flow | Collect affordance from video | Paper | Code |
PreAffordance | Pre-grasping planning | Paper | |
ScenFun3d | Fine-grained functionality | Paper | Code |
Description | Paper | Code | |
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COPA | Paper | ||
ManipLLM | Paper | ||
ManipVQA | Paper | Code |
Description | Paper | Code | |
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OLAF | Paper | ||
YAYRobot | Paper | Code |
Description | Paper | Code | |
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SayCan | API Level | Paper | Code |
VILA | Prompt Level | Paper |
- Genesis - Genesis is a physics platform designed for general-purpose Robotics/Embodied AI/Physical AI applications. It is simultaneously multiple things: A universal physics engine re-built from the ground up, capable of simulating a wide range of materials and physical phenomena.; A lightweight, ultra-fast, pythonic, and user-friendly robotics simulation platform. [⭐22747]
- Habitat Sim - A flexible, high-performance 3D simulator for Embodied AI research. Habitat-Sim is typically used with Habitat-Lab, a modular high-level library for end-to-end experiments in embodied AI. [⭐5000]
- Isaac Sim - NVIDIA Isaac Sim™ is a reference application built on NVIDIA Omniverse that enables developers to simulate and test AI-driven robotics solutions in physically based virtual environments.
- MuJoCo - Physics engine for robotics, biomechanics, and graphics
- PyBullet - Physics simulation for robotics and machine learning
- Gazebo - Robot simulation environment
- SAPIEN - A SimulAted Part-based Interactive ENvironment
- Webots - Webots is an open source and multi-platform desktop application used to simulate robots. It provides a complete development environment to model, program and simulate robots.
- AnyTeleop - A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System
- Dex Retargeting - Various retargeting optimizers to translate human hand motion to robot hand motion.
- ChatTTS - A generative speech model for daily dialogue
- Real3D-Portrait - One-shot Realistic 3D Talking Portrait Synthesis
- Hallo2 - Long-Duration and High-Resolution Audio-driven Portrait Image Animation
- MoveIt - Motion planning framework
- OMPL - Open Motion Planning Library
- Drake - Planning and control toolkit
- GR-1 - ByteDance Research: Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation
- Universal Manipulation Interface(UMI)
- Meta Motivo - A first-of-its-kind behavioral foundation model to control a virtual physics-based humanoid agent for a wide range of whole-body tasks.
- OpenVLA - OpenVLA sets a new state of the art for generalist robot manipulation policies. It supports controlling multiple robots out of the box and can be quickly adapted to new robot setups via parameter-efficient fine-tuning.
- RoboNet - Large-scale robot manipulation dataset
- BEHAVIOR-1K - Dataset of human household activities
- Google Robot Data - Various robotics datasets
- Contact-GraspNet - Dataset for robotic grasping
- AMASS - Large human motion dataset
- Human3.6M - Large-scale dataset for human sensing
- CMU Graphics Lab Motion Capture Database
- CALVIN - CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
- DexYCB - A Benchmark for Capturing Hand Grasping of Objects
- Berkeley AI Research (BAIR)
- Stanford Robotics & Embodied Artificial Intelligence Lab (REAL)
- MIT CSAIL
- Google Research
- UT Austin Robot Perception and Learning Lab (RPL)
- Boston Dynamics
- Agility Robotics
- Figure AI
- 1X Technologies
- Sanctuary AI
- Fourier Intelligence [Github] [Docs]
- AgiBot Github
- Atlas - Advanced humanoid robot by Boston Dynamics
- Digit - Bipedal robot by Agility Robotics
- Tesla Optimus - Tesla's humanoid robot project
- Figure 01 - General purpose humanoid robot
- Phoenix - Open-source humanoid robot design
- Fourier GR-2 - Fourier General Purpose Humanoid Robotics
- OKAMI: Teaching Humanoid Robots Manipulation Skills through Single Video Imitation
- GR-MG: Leveraging Partially Annotated Data via Multi-Modal Goal Conditioned Policy
- RSS - Robotics: Science and Systems
- ICRA - International Conference on Robotics and Automation
- CoRL - Conference on Robot Learning
- IROS - International Conference on Intelligent Robots and Systems
Please read the contribution guidelines before making a contribution.
This project is licensed under the MIT License - see the LICENSE file for details.