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README.md

动手做具身智能：从算法到实机部署的“通关”实践指南

作者：Brain实验室

一、机器人基础操作与硬件集成

二、机器人全身运动控制

  • 具体教程：
    • 2.1 基于Isaac Gym的基础步态训练, link
    • 2.2 运动数据采集（一）：基于人类演示视频的GVHMR, link
    • 2.3 运动数据采集（二）：基于动作捕捉的GMR, link
    • 2.4 运动策略生成（一）：基于ASAP & PBHC, link
    • 2.5 运动策略生成（二）：基于Beyond MIMIC, link
    • 2.6 运动策略板载部署：基于RoboJuDo, link
  • 参考文献：
  • 软件工具：
    • unitree_rl_gym, is a repository for reinforcement learning implementation based on Unitree robots, supporting Unitree Go2, H1, H1_2, and G1, code
    • HumanoidVerse, is a multi-simulator framework for humanoid robot sim-to-real learning, code
  • 硬件设备：

三、机器人操作数据采集

  • 具体教程：
    • 3.1 机器人半身遥操作：基于XR Teleoperate框架, link
    • 3.2 机器人全身遥操作：基于TWIST框架, link
  • 参考文献：
  • 软件工具：
    • xr_teleoperate, aims to implement teleoperation control of a Unitree humanoid robot using XR devices (such as Apple Vision Pro, PICO 4 Ultra Enterprise, or Meta Quest 3), code
  • 硬件设备：

四、机器人环境感知与建模

五、机器人视觉语言导航

  • 具体教程：
    • 5.1 基于OpenNav的视觉语言导航, link
    • 5.2 基于NaVILA的视觉语言导航, link
    • 5.3 基于InternNav的视觉语言导航, link
  • 参考文献：
    • ICRA 2025, SpatialBot: Precise Spatial Understanding with Vision Language Models, code
    • RSS 2025, NaVILA: Legged Robot Vision-Language-Action Model for Navigation, website / code / model
    • 2025.09, InternVLA-N1: An Open Dual-System Vision-Language Navigation Foundation Model with Learned Latent Plans, website / code
    • arXiv 2025.05, NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidance, website
    • arXiv 2024.09, Open-nav: Exploring zero-shot vision-and-language navigation in continuous environment with open-source llms, website / code
    • arXiv 2024.06, Depth Anything V2, website / code
    • CVPRW 2024, Recognize Anything: A Strong Image Tagging Model, website / code
    • CVPR 2022, Bridging the Gap Between Learning in Discrete and Continuous Environments for Vision-and-Language Navigation, code
    • ECCV 2020, Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments, website / code
  • 软件工具：
    • Habitat-Sim, a flexible, high-performance 3D simulator for embodied AI research, website / code
    • Habitat-Lab, a modular high-level library to train embodied AI agents across a variety of tasks and environments, website / code

六、机器人视觉语言操作

  • 具体教程：
    • 6.1 Unitree LeRobot框架介绍及配置, link
    • 6.2 Unitree LeRobot数据格式及转换, link
    • 6.3 Unitree LeRobot典型模型库介绍, link
    • 6.4 Unitree LeRobot训练与工程测试, link
    • 6.5 NVIDIA GR00T模型微调, link
    • 6.6 NVIDIA GR00T工程实践, link
  • 参考文献：
  • 软件工具：
    • LeRobot, aims to provide models, datasets, and tools for real-world robotics in PyTorch, website / code
    • unitree_IL_lerobot, is a modification of the LeRobot open-source training framework, enabling the training and testing of data collected using the dual-arm dexterous hands of Unitree's G1 robot, code
    • xr_teleoperate, aims to implement teleoperation control of a Unitree humanoid robot using XR devices (such as Apple Vision Pro, PICO 4 Ultra Enterprise, or Meta Quest 3), code

七、机器人人机交互系统

  • 具体教程：
    • 7.1 宇树原生交互系统介绍, link
    • 7.2 外接大模型的集成方法, link
    • 7.3 本地知识库构建与接入方案, link
    • 7.4 机器人导游与导览应用概述, link
  • 软件工具：
  • 硬件设备：

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