网页端依赖自建 Supabase 项目做认证和存储,需先跑 SQL 迁移并填 API key;默认通过 80 端口访问,若选 g1-internal 则改为 3000 端口;YOLO 检测和检测历史等 AI 功能 README 标注为即将推出,尚不可用。

BotBrain
botbotroboticsMIT更新放缓给四足和人形机器人用的模块化开源大脑,带 Web 界面做遥操作、自主导航、建图和监控,配套可 3D 打印硬件,跑在 ROS2 上。
Modular open-source brain for legged robots. Web UI for teleops, autonomous navigation, mapping & monitoring. 3D-printable hardware that runs on ROS2.
git clone https://github.com/botbotrobotics/BotBrain.git
cd BotBrain
sudo ./install.sh
sudo reboot围绕 NVIDIA Jetson 设计,官方支持 Jetson Nano 和 Orin Nano,AGX 与 Thor 即将支持;部分重型 AI 模块需要 Orin AGX。传感器按 Intel RealSense D435i 设计,双相机用于查看与 SLAM。推荐系统为 NVIDIA JetPack 6.2。
给腿足和轮式 ROS2 机器人装一个开源大脑,用网页就能遥控、建图、导航和监控
给四足和人形机器人用的模块化开源大脑,带 Web 界面做遥操作、自主导航、建图和监控,配套可 3D 打印硬件,跑在 ROS2 上。
核心能力
- 用 Next.js 网页界面统一遥控、看相机和地图
- 基于 RTABMap 做视觉 SLAM,Nav2 负责路径规划与避障
- 支持多航点任务规划,在地图上点击即可导航
- 按优先级仲裁速度指令,并带急停与死人开关
- 提供可 3D 打印外壳和机器人专用安装转接件
容易踩的坑
暂无 release 数据(可能没有发版,或尚未同步)。
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
BotBrain Open Source (BBOSS)
BotBrain is a modular collection of open source software and hardware components that lets you drive, see, map, navigate (manually or autonomously), monitor, and manage legged (quadrupeds, bipeds and humanoids) or wheeled ROS2 robots from a simple but powerful web UI. The hardware gives you 3D printable mounts and an outer case so you can put BotBrain on your robot without guesswork.
- Designed around Intel RealSense D435i and the NVIDIA Jetson line
- Officially supported boards: Jetson Nano, Jetson Orin Nano (support for AGX and Thor coming soon)
- Everything is modular - you don't need to run every module (some heavy AI modules require Orin AGX)
Compleate features list
Multi-Robot Platform Support
- Unitree Go2 & Go2-W - Quadruped robots with full hardware interface and control
- Unitree G1 - Humanoid with upper-body pose control and FSM transitions
- DirectDrive Tita - Biped with full control
- Custom robots - Extensible framework for adding any ROS2-compatible platform
- Legged & wheeled - Architecture supports both locomotion types
Hardware & Sensors
- 3D printable enclosure - Snap-fit design with robot-specific mounting adapters (Go2, G1, and Direct drive Tita)
- Intel RealSense D435i - Dual camera support for viewing and SLAM/Navigation
- IMU & odometry - Real-time pose estimation from all supported platforms
- Battery monitoring - Per-robot battery state with runtime estimation
AI & Perception (Coming Soon)
- YOLOv8/v11 object detection - 80+ classes, TensorRT-optimized, real-time tracking on BotBrain (Coming Soon)
- ROSA natural language control - Conversational robot commands via LLM
- Detection history - Searchable log with image and information / description (Coming Soon)
Autonomous Navigation
- RTABMap SLAM - Visual mapping with single or dual RealSense D435i cameras
- Nav2 integration - Path planning, dynamic obstacle avoidance, recovery behaviors
- Mission planning - Create and execute multi-waypoint autonomous patrols
- Click-to-navigate - Set goals directly on the map interface
- Map management - Save, load, switch, and set home positions
System Orchestration
- Lifecycle management - Coordinated node startup/shutdown with dependency ordering
- State machine - system states with automatic on/off
- Priority-based velocity control - 6-level command arbitration (joystick > nav > AI)
- Dead-man switch - Hardware/software safety lock for all motion commands
- Emergency stop - Comprehensive e-stop sequence
Control Interfaces
- CockPit - Pre-configured control page with cameras, 3D model, map, and quick actions
- My UI - Drag-and-drop customizable dashboard with resizable widgets
- Virtual joysticks - Touch/mouse dual-stick control with velocity tuning
- Gamepad support - PS5, Xbox or generic joystick with custom button mapping and mode switching
- Keyboard control - WASD controls
- Speed profiles - Multiple velocity presets for different operational modes (Beginner, Normal and Insane mode)
- Robot actions - Stand/sit, lock/unlock, gait selection, lights, mode transitions
Camera & Video
- Multi-camera streaming - Dynamic discovery for front, rear, and custom topics
- H.264/H.265 codecs - Resolution scaling, frame rate control, bandwidth optimization
- In-browser recording - Record video from cameras and save them to your downloads folder
- 3D visualization - URDF-based robot model with laser scan overlay and navigation path
System Monitoring
- Jetson stats - Board model, JetPack version, power mode, uptime
- CPU/GPU monitoring - Per-core usage, frequency, memory, thermal throttling
- Power tracking - Per-rail voltage, current, and wattage with peak detection
- Thermals & fans - CPU/GPU/SOC temps with fan speed control
- Storage & memory - Disk usage alerts, RAM/swap monitoring
Networking & Fleet
- WiFi control panel - Network scanning, switching, and signal monitoring
- Connection modes - WiFi, Ethernet, 4G, hotspot with latency tracking
- Multi-robot fleet - Simultaneous connections, fleet-wide commands, status dashboard
- Diagnostics - Node health, error/warning logs, state machine visualization
Customization & UX
- Light/dark themes - Custom accent colors, persistent preferences
- Responsive layouts - Mobile, tablet, and desktop with touch support
- User profiles - Avatar, display name, theme color via Supabase Auth
- Multi-language - English and Portuguese with regional formats
- Audit logging - Searchable event history across 10+ categories with CSV export
- Activity analytics - Usage heatmaps and robot utilization tracking
Table of Contents
- Overview
- Project Structure
- Requirements
- Installation
- Frontend Development
- Features
- Configuration
- Custom Robots
- Troubleshooting
- Contributing
- License
Overview
BotBrain consists of three main components:
Hardware
A 3D printable enclosure with internal mounts designed to house an NVIDIA Jetson board and two Intel RealSense D435i cameras. The modular design allows you to attach BotBrain to various robot platforms without custom fabrication.
Frontend
A Next.js 15 web dashboard built with React 19 and TypeScript. It provides real-time robot control, camera streaming, map visualization, mission planning, system monitoring, and fleet management—all accessible from any browser on your network.
Robot (ROS2 Workspace)
A collection of ROS2 Humble packages that handle:
- Bringup & Orchestration (
bot_bringup) - System launch and coordination - Localization (
bot_localization) - RTABMap-based SLAM for mapping and positioning - Navigation (
bot_navigation) - Nav2 integration for autonomous movement - Perception (
bot_yolo) - YOLOv8/v11 object detection - Robot Drivers - Platform-specific packages for Unitree Go2/G1, DirectDrive Tita, and custom robots
Project Structure
BotBrain/
├── frontend/ # Next.js 15 web dashboard (React 19, TypeScript)
├── botbrain_ws/ # ROS 2 Humble workspace
│ └── src/
│ ├── bot_bringup/ # Main launch & system orchestration
│ ├── bot_custom_interfaces/# Custom ROS 2 messages, services, actions
│ ├── bot_description/ # URDF/XACRO models & robot_state_publisher
│ ├── bot_jetson_stats/ # Jetson hardware monitoring
│ ├── bot_localization/ # RTABMap SLAM
│ ├── bot_navigation/ # Nav2 autonomous navigation
│ ├── bot_rosa/ # ROSA AI natural language control
│ ├── bot_state_machine/ # Lifecycle & state management
│ ├── bot_yolo/ # YOLOv8/v11 object detection
│ ├── g1_pkg/ # Unitree G1 support
│ ├── go2_pkg/ # Unitree Go2 support
│ ├── joystick-bot/ # Game controller interface
│ └── tita_pkg/ # DirectDrive Tita robot support
├── hardware/ # 3D printable enclosure (STL/STEP/3MF)
└── docs/ # Documentation
Requirements
Hardware
| Component | Requirement |
|---|---|
| Compute | NVIDIA Jetson (Nano, Orin Nano, or AGX series) |
| Cameras | 2x Intel RealSense D435i |
| Robot | ROS2 Humble robot or Unitree Go2 and Go2-W, Unitree G1, Direct Drive Tita, or custom robot |
| Network | Ethernet or WiFi connection |
Software
| Component | Requirement |
|---|---|
| OS | JetPack 6.2 (Ubuntu 22.04) recommended |
| Container | Docker & Docker Compose |
| Node.js | v20+ (for local frontend development only) |
Installation
BotBrain has two main components: hardware (3D printed enclosure and internal components) and software (frontend web app and ROS2 workspace).
1. Hardware Setup
3D print the enclosure and assemble the electronics.
Key Parts: 3D printer, PLA filament, NVIDIA Jetson, 2x RealSense D435i, voltage converter.
Hardware Assembly Guide - Detailed instructions on how to build your BotBrain
Complete Assembly Video - Full step-by-step video walkthrough of the BotBrain assembly process
2. Supabase Setup
The web dashboard requires Supabase for authentication and data storage. You'll need to create your own free Supabase project.
Supabase Setup Guide - Complete instructions with database schema
Quick summary:
- Create a project at supabase.com
- Run the SQL migrations from the setup guide
- Copy your API keys for the next step
3. Software Setup
G1 WiFi Setup Guide - If you are using G1 robot, please refeer to this docs before.
External Dependencies
Operating System:
- NVIDIA JetPack 6.2 (recommended)
- Other Linux distributions may work but are not officially supported
Docker & Docker Compose:
Required for containerized deployment:
- Install Docker:
# Add Docker's official GPG key:
sudo apt-get update
sudo apt-get install ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
# Add the repository to Apt sources:
echo \
"deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
$(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update
# Install Docker packages:
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin
See official Docker installation guide for more details.
- Enable Docker without sudo:
sudo groupadd docker
sudo usermod -aG docker $USER
newgrp docker
See post-installation steps for more details.
Installation Steps
Step 1: Clone the Repository
git clone https://github.com/botbotrobotics/BotBrain.git
cd BotBrain
Step 2: Run Installation Script
The automated installation script will configure your robot and set up the autostart service:
sudo ./install.sh
More details about the information asked in the installer can be found here
Step 3: Reboot the System
sudo reboot
Once rebooted, the system will automatically start the Docker containers for all ROS2 nodes and the web server.
Step 4: Access the Web Interface
| Access Method | URL |
|---|---|
| Same computer | http://localhost |
| Network access | http://<JETSON_IP> |
Find your Jetson's IP address:
hostname -I
Note: Ensure both devices are on the same network and port 80 is not blocked by a firewall.
Note: Also if you selected g1-internal, your web port will be 3000. So your web ip will be: http://<JETSON_IP>:3000
Frontend Development
For local frontend development (without the full robot stack):
Setup
cd frontend
# Copy environment template
cp .env.example .env.local
# Edit with your Supabase credentials
nano .env.local
Environment Variables
| Variable | Required | Description |
|---|---|---|
NEXT_PUBLIC_SUPABASE_URL | Yes | Your Supabase project URL |
NEXT_PUBLIC_SUPABASE_ANON_KEY | Yes | Your Supabase anon/public key |
NEXT_PUBLIC_ROS_IP | No | Default robot IP (default: 192.168.1.95) |
NEXT_PUBLIC_ROS_PORT | No | ROS bridge port (default: 9090) |
Running
# Install dependencies
npm install
# Development server (full features)
npm run dev
# Development server (open source edition)
npm run dev:oss
# Production build
npm run build
npm start
Configuration
Robot Configuration
Edit botbrain_ws/robot_config.yaml:
robot_configuration:
robot_name: "my_robot" # Namespace for all topics
robot_model: "go2" # go2, tita, g1, or custom
network_interface: "eth0" # Network interface for ROS2
openai_api_key: "" # For AI features (optional)
Camera Configuration
Camera serial numbers and transforms are configured per robot in:
botbrain_ws/src/go2_pkg/config/camera_config.yamlbotbrain_ws/src/g1_pkg/config/camera_config.yamlbotbrain_ws/src/tita_pkg/config/camera_config.yaml
Find your camera serial numbers:
rs-enumerate-devices | grep "Serial Number"
Add Support for Other Robots / Custom Robots
To add support for a new robot platform to BotBrain:
- Backend/ROS2 Stack: Follow the comprehensive Creating a Custom Robot Package guide
- Frontend: Add a robot profile in the web interface settings
Troubleshooting
WebSocket Connection Failed
- Verify rosbridge is running:
ros2 node list | grep rosbridge - Check firewall allows port 9090:
sudo ufw allow 9090 - Ensure correct IP in robot connection settings in the UI
Camera Not Detected
- List connected cameras:
rs-enumerate-devices - Check USB connections and ensure cameras have power
- Verify serial numbers in
camera_config.yamlmatch your cameras - Check USB permissions:
sudo usermod -a -G video $USER
Docker Issues
- Ensure Docker runs without sudo (see installation instructions)
- Check GPU access:
docker run --gpus all nvidia/cuda:11.0-base nvidia-smi - View container logs:
docker compose logs -f bringup
Frontend Not Loading
- Verify Supabase credentials in
.env.local - Check browser console for errors
- Ensure Node.js v20+ is installed:
node --version
Robot Not Moving
- Check twist_mux is running:
ros2 topic echo /cmd_vel_out - Verify robot hardware interface is active:
ros2 lifecycle get /robot_write_node - Check for emergency stop engaged in the UI
Need More Help?
Join our Discord community for real-time support and discussions with the BotBrain community.
Contributing
We welcome contributions! Whether you're fixing bugs, adding features, improving documentation, or adding support for new robots, your help is appreciated. If you can make BotBrain better or faster, bring it.
Join our Discord server to discuss ideas, get help, or coordinate with other contributors.
Development Workflow
-
Fork the Repository
# Fork via GitHub UI, then clone your fork git clone https://github.com/botbotrobotics/BotBrain.git cd BotBrain -
Create a Feature Branch
git checkout -b feature/your-amazing-feature -
Make Your Changes
- Add tests for new functionality
- Update relevant README files
- Ensure all packages build successfully
- Follow ROS 2 coding standards
-
Test Thoroughly
-
Commit Your Changes
git add . git commit -m "Add feature: brief description of changes" -
Push to Your Fork
git push origin feature/your-amazing-feature -
Submit a Pull Request
- Provide a clear description of your changes
- Reference any related issues
- Include screenshots or videos for UI/behavior changes
BotBrain Pro
Professional / Enterprise version of BotBrain with IP67 protection, custom payloads like CamCam (Thermal + infrared Camera), ZoomZoom (long range 30x RGB camera), advanced AI models, IoT integration (LoRA), 3-5g data connectivity, service and maintianance, advanced integrations with custom payloads, and much more. Learn more here or book your test drive now.
Safety
Robots can hurt people and themselves when operated incorrectly or during development. Please observe these safety practices:
- Use a physical E-stop - Never rely solely on software stops
- Rotate API keys if they leak
- Test changes in simulation before running on physical hardware
- Keep clear of the robot during initial testing
Disclaimer: BotBot is not responsible for any failures, accidents, or damages resulting from the use of this software or hardware. The user assumes full responsibility for the safe operation, testing, and deployment of robots using BotBrain.
Third-Party Libraries
See docs/DEPENDENCIES.md for a complete list of frontend and ROS packages used.
License
This project is licensed under the MIT License - see the LICENSE file for details.