This project consists of two main components: a robot dog backend system and a mobile EEG application. The system allows users to control a robot dog using brain signals captured through EEG (Electroencephalography).
The backend system is built using Python and runs on a Raspberry Pi 5. It handles:
- Bluetooth communication with the EEG headset
- Robot dog control using the Unitree GO1 API
- Real-time data processing and command execution
- WebSocket server for real-time communication with the mobile app
Key features:
- High-level control of the Unitree GO1 robot dog
- Bluetooth connectivity for EEG data acquisition
- Real-time command processing
- Safety protocols and error handling
The mobile application is built using Flutter and provides:
- Real-time EEG data visualization
- User interface for controlling the robot dog
- Connection management with the backend
- Data logging and analysis
Key features:
- Cross-platform support (iOS and Android)
- Real-time EEG signal processing
- Intuitive control interface
- Data visualization and analysis tools
- Raspberry Pi 5
- Unitree GO1 robot dog
- EEG headset with Bluetooth capability
- Flutter development environment
- Python 3.x
- Clone the repository
- Navigate to the
robot_backenddirectory - Install dependencies:
pip install -r requirements.txt
- Configure the Bluetooth settings
- Start the backend server:
python app.py
- Navigate to the
eeg_appdirectory - Install Flutter dependencies:
flutter pub get
- Run the app:
flutter run
- Power on the robot dog
- Start the backend server on the Raspberry Pi
- Launch the mobile app
- Connect the EEG headset
- Use the app interface to control the robot dog
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.