Get Started with Raspberry Pi Blockset
Raspberry Pi® Blockset provides blocks and functions in MATLAB® and Simulink® for prototyping and implementing applications on Raspberry Pi hardware. You can interface with hardware peripherals such as GPIO, I2C, SPI, and camera modules for rapid prototyping.
With Raspberry Pi Blockset, you can acquire sensor data, control actuators, and build applications for image and audio processing, signal processing, and Internet of Things (IoT) systems. You can also deploy machine learning or deep learning applications for edge computing on Raspberry Pi.
You can develop algorithms in MATLAB and Simulink and deploy them to Raspberry Pi using automatic code generation (with Embedded Coder®). The blockset supports live parameter tuning, signal monitoring, and connected I/O workflows, enabling real-time interaction with hardware.
Tutorials
- Working with Raspberry Pi Hardware
This example shows basics of how to work with Raspberry Pi® Hardware.
- Connect to and Control Raspberry Pi Board from MATLAB
This example shows you how to use Raspberry Pi® Blockset to perform basic operations on hardware such as executing shell commands, turning an on-board LED on or off, and manipulating files using installed MATLAB®.
- Deploy and Run Custom MATLAB Functions on Raspberry Pi
This example shows how to deploy a MATLAB® function as a standalone executable on the Raspberry Pi® Hardware using Raspberry Pi Blockset.
- Build and Deploy Your First Simulink Model to Raspberry Pi
This example shows you how to use Raspberry Pi® Blockset to build and deploy a Simulink® model on Raspberry Pi hardware.
- Product Stack for Raspberry Pi Blockset
Identify minimum required product(s) for Raspberry Pi Blockset to best suit your end goals. - Get IP Address of Raspberry Pi Hardware
You can use any of these methods to know the IP address of your Raspberry Pi hardware. - Configure Network Settings of Raspberry Pi Hardware
Configure the network settings of your Raspberry Pi hardware.
Raspberry Pi Blockset Basics
Featured Examples
Classify Objects Using Deep Learning Algorithm on Raspberry Pi Hardware
Use the Raspberry Pi® Blockset Hardware to deploy a deep learning algorithm that classifies objects using the ResNet-50 convolutional neural network. This pretrained network is 50 layers deep and can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many more. You can experiment with different objects in your surroundings to see how accurately the network classifies images on the Raspberry Pi hardware.
Get Started with Sensors for Robotics Applications Using Raspberry Pi and Simulink Online
Use Raspberry Pi® Blockset and a Raspberry Pi hardware board to get started with the driver blocks for commonly used robotics sensors.
Configure Image and Device Properties of Raspberry Pi V4L2 Video Capture Block to Detect Objects
Configure the image and device properties of the V4L2 Video Capture block from Raspberry Pi® Blockset and observe the output in the SDL Video Display block. This example also shows how to tune the image properties of the V4L2 Video Capture block to detect objects in a noisy and distorted real-time video.
Get Started with Audio Signal Processing Using Raspberry Pi
Use Raspberry Pi® Blockset to get started with audio signal processing applications on the Raspberry Pi hardware. It also shows how to:
Log CAN Bus Data on Raspberry Pi
Use Raspberry Pi® Blockset to monitor a controller area network (CAN) bus, perform basic CAN conversions, and log CAN data in a measurable data format (MDF) file. This example also showcases the inter-operability between a model deployed in Simulink® and a Python® program running simultaneously on Raspberry Pi hardware.
Publish and Subscribe to Messages on ThingSpeak Using MQTT Blocks on Raspberry Pi
Use Raspberry Pi® Blockset to publish a message to a topic from Raspberry Pi in the ThingSpeak™ MQTT broker. This example also shows how to subscribe to a topic and receive a message from the ThingSpeak MQTT broker to Raspberry Pi. For more information on MQTT protocol, see MQTT Basics (ThingSpeak) and Publish MQTT Messages and Subscribe to Message Topics. In this example, ThingSpeak is the MQTT broker and Raspberry Pi board is the MQTT client (publisher and subscriber).
Get Started with Deploying Web-Based Customizable Dashboard Blocks on Raspberry Pi
Use Raspberry Pi® Blockset to create an interactive dashboard display using the Dashboard (Simulink) Circular Gauge (Simulink) and Knob (Simulink) blocks from the Simulink Customizable Blocks library. The example also shows you how to deploy the interactive dashboard on your Raspberry Pi hardware board. You can customize the visual aspects of the dashboard widgets so that the dashboard looks like a real system. You can obtain the what you see is what you get (WYSIWYG) visualization on a web browser or a display connected to the Raspberry Pi hardware.
