A project that aims to primarily control LEGO SPIKE with a Raspberry Pi.
It uses the mpremote tool to communicate with the LEGO SPIKE hub.
See this Youtube video for an introduction and demonstration of the project.
The simplest way to install SpiBerryEngine is from PyPI:
pip install spiberry-engineFor vision support (OpenCV/Ultralytics) and camera features:
pip install "spiberry-engine[full]"Other extras:
spiberry-engine[vision]- Vision features (OpenCV/Ultralytics)spiberry-engine[camera]- Camera capture featuresspiberry-engine[controller]- Remote drive controller features
After installation, initialize your environment (creates config and default robot code):
spiberry initTransfer the spiberry.pyz file to your Raspberry Pi and run it:
python spiberry.pyzIt will create a virtual environment and install dependencies. Service installation is explicit via the --install-service flag.
Install and optionally start the service from the installer flow:
sudo python spiberry.pyz --install-service --start-serviceConnect the following components to your Raspberry Pi:
- Starter Pin: Must be connected to ground (GPIO 21 by default) to start the program. You can bypass this by setting the environment variable
IGNORE_STARTER_PIN=1. - RGB LED: Connect to the GPIO pins specified during initialization or defaults:
- Red: GPIO 0
- Green: GPIO 11
- Blue: GPIO 9
You can disable the RGB LED by setting
rgb_led_enabled = Falseunder[GPIO]in the config file.
- Button: Connect to GPIO pin specified (default: 17)
When installed via PyPI, several commands are available:
| Command | Description |
|---|---|
spiberry init |
Initialize default config and robot code |
spiberry run-engine |
Run the main engine |
spiberry-start |
Start the systemd service |
spiberry-stop |
Stop the systemd service |
spiberry-status |
Check service status |
spiberry-remote-drive |
Start remote drive controller |
To run the engine manually with the default configuration:
spiberry run-engineYou can also specify a custom robot code file:
spiberry run-engine my_cool_robot.pySpiBerryEngine stores runtime settings in:
~/spiberry_config.ini
On first run or with the spiberry init command, this file is created automatically with defaults similar to:
[GPIO]
red = 0
green = 11
blue = 9
button = 17
active_high = False
[Code]
path = robot_code.py
raspi_functions_path = raspi_functions/
[Vision]
enabled = False
[Camera]
take_picture_method = picamera2
timeout = 0
width = 1920
height = 1080
[RemoteDrive]
left_motor = port.A
right_motor = port.BNotes:
Code.pathcontrols which robot code file is executed.Code.raspi_functions_pathcan point to either:- a Python file (for example
raspi_functions.py), or - a package directory (for example
raspi_functions/, using__init__.py).
- a Python file (for example
- Vision features are only loaded when
Vision.enabled = True. RemoteDrive.left_motorandRemoteDrive.right_motorset default motor ports for remote drive mode.
CLI GPIO pin arguments are now persisted into the config file when provided:
# Example if running standalone
python spiberry.pyz --red 0 --green 11 --blue 9 --button 17The values are then saved under [GPIO].
Note: See the VS Code Extension for easier installation and code deployment. The extension provides a user-friendly interface, and is recommended.
Recommended method: Use the VS Code Extension
Use deploy_robot_code.py to deploy your robot code:
- Run the deploy tool on your computer
- Select your
.llsp3file (LEGO SPIKE project export) - Optionally select a Raspi Functions file (see below)
- Enter your Raspberry Pi connection details
- Click "Deploy" or use the hotkey
Ctrl+Shift+D
The deployer will:
- Extract your code from the
.llsp3file - Send
robot_code.pyto your Raspberry Pi - Optionally send
raspi_functions.pyif provided - Save your configuration for future deployments
Copy the contents of raspi-util-class.py and paste it at the top of your robot code. This provides easy-to-use classes for interacting with Raspberry Pi hardware from your LEGO SPIKE code.
# Copy raspi-util-class.py contents here at the top of your code
# Create Raspi instance
raspi = Raspi()
# Register devices
servo = raspi.register_device("servo", "s1", "14","0","180","0.00095","0.0028","10")
# Parameters are: type, name, pin, min_angle, max_angle, min_pulse, max_pulse, start_angle
distance_sensor = raspi.register_device("distance_sensor", "my_sensor", "15", "16", "4")
# Parameters are: type, name, trigger_pin, echo_pin, max_distance_m
# Use devices
servo.set_angle(90)
current_angle = servo.get_angle()
distance = distance_sensor.get_distance()
# Call custom functions (if you have raspi_functions.py)
result = raspi.my_custom_function() # Preferred way to call custom functions
result = raspi.func("some_custom_function()") # Deprecated, may be removed in future versionsThe utility classes support:
- Servo:
set_angle(angle),get_angle() - Distance Sensor:
get_distance() - Custom Functions:
raspi.my_custom_function()to call functions from yourraspi_functions.py
The RGB LED provides visual feedback for the system state:
| Color | Meaning |
|---|---|
| Red | Connection error or module not found |
| Green | Ready/Idle/Success |
| Blue | Run Error |
| Yellow | Work starting |
| Cyan | Code or functions reloaded |
| Color | Blink Count | Blink Duration | Meaning |
|---|---|---|---|
| Red | 2 | 0.2s | raspi_functions import error |
| Red | 2 | 0.2s | Stopped code execution |
| Red | 5 | 0.1s | mpremote not found |
| Red | 5 | 0.3s | Connection error |
| Blue | 2 | 0.1s | REPL error |
| Blue | 2 | 0.3s | Function call function not found error |
| Blue | 5 | 0.1s | Code execution error |
| Green | 2 | 0.2s | Code started/stopped/ended |
| Cyan | 2 | 0.2s | Code reloaded |
| Cyan | 3 | 0.2s | Functions reloaded |
| Cyan | 5 | 0.2s | Functions & Code reloaded |
SpiBerryEngine supports two camera capture methods: picamera2 (recommended for Raspberry Pi OS) and rpicam-still (command-line tool). Both methods support comprehensive configuration options.
See examples/camera_config_examples.py for comprehensive examples and the picamera2 manual and rpicam-still documentation for complete option lists.
SpiBerryEngine includes a Vision and ContourDetector classes that provides some image processing capabilities using OpenCV and object detection using Ultralytics. You can use the take_picture() method to capture an image and then apply various processing methods like detect_objects(), find_contours(), or custom OpenCV operations.
See examples/vision_examples.py for usage examples.
main.py- Main engine scriptvision.py- Vision processing classes (Vision, ContourDetector)camera.py- Camera capture classesremote_drive/- Remote drive control module (client and controller)installer.py- (deprecated) Installation script with GUIdeploy_robot_code.py- (deprecated) Code deployment tool with GUIsbe.service- Systemd service configurationrequirements.txt- Python dependenciesscripts/- Helper scripts for service management
- Raspberry Pi GPIO pins for RGB LED and Button
- LEGO SPIKE Hub connected via USB to Raspberry Pi
- Raspberry Pi running Raspberry Pi OS with Python 3
- Check the RGB LED signals for error codes
- Ensure all dependencies are installed
- Ensure there is no syntax error in your robot code (Spike App does not always show them)
- Check your installation and code deployment paths
This project is an independent community project and is not affiliated with, endorsed by, or sponsored by LEGO Group or Raspberry Pi Ltd. Use at your own risk. Always follow safety guidelines when working with hardware.