モデル化

チュートリアル

外部周辺デバイスを使用した適用例

• Communicate with EEPROM Using Raspberry Pi
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware to read from and write to an SPI EEPROM.
• Read Temperature from TMP102 Sensor Using Raspberry Pi
  This example illustrates how to use Simulink® Support Package for Raspberry Pi® Hardware to configure and read temperature from a TMP102 sensor.
• Trigger Downstream Function-Call Subsystem Using Raspberry Pi External Interrupt Block
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to trigger a downstream function-call in the connected IO mode and external mode of simulation (Monitor and Tune) using a Raspberry Pi External Interrupt block. This example provides two Simulink models, one each for connected IO mode and external mode of simulation, to show the capabilities of the External Interrupt block in each of the modes.
• Trigger Downstream Function-Call Subsystem Using Raspberry Pi External Interrupt Block with Single Tap Event on BMI160 Sensor
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to trigger a downstream function-call in Monitor and Tune action when single tap event occurs on the BMI160 sensor using a Raspberry Pi External Interrupt block. This example model for monitor and tune simulation showcases the capabilities of the External Interrupt block during a single tap event on the BMI160 sensor.

Sense HAT ブロックを使用した適用例

• Auto-Rotate Image Displayed on Raspberry Pi Sense HAT LED Matrix
  This example shows you how to develop a Simulink® model to implement an algorithm to read the Accelerometer On-board Sense HAT and control the rotation of the image displayed on the LED matrix.
• Control LEGO MINDSTORMS EV3 Robot Using Raspberry Pi Sense HAT
  This example shows how to read the Accelerometer on Raspberry Pi® Sense HAT and use this data to control the motion of a LEGO® MINDSTORMS® EV3 robot.
• Count Steps Using Raspberry Pi Sense HAT
  This example demonstrates an application that counts the number of steps a person walked while holding a Raspberry Pi® Sense HAT.
• Simulate Audio Visualizer on Raspberry Pi Sense HAT
  This example shows how to simulate an audio visualizer on Sense HAT using the Simulink® Support Package for Raspberry Pi® Hardware.
• Publish Data from Raspberry Pi Sense HAT to WebSocket Server
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware to publish the signals obtained from a Raspberry Pi Sense HAT to a WebSocket server, and read the data on a web browser in the WebSocket client.
• Control Color of LED Matrix on Raspberry Pi Sense HAT over WebSockets
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to control the color of an 8x8 LED matrix on Raspberry Pi Sense HAT from a web page over WebSockets.

ROS を使用した適用例

• Get Started with Robot Operating System on Raspberry Pi
  This example shows you how to build a standalone robot operating system (ROS) node from a Simulink® model on a Raspberry Pi® hardware board.
• Stream Images from Raspberry Pi Using Robot Operating System
  This example shows how to stream images captured from a webcam on a Raspberry Pi® board to the host computer using a ROS communication interface. In this example, you stream images from your Raspberry Pi board to your host computer using the ROS Publish blocks. You use the ROS MATLAB® command line interface to display the images on your host computer.
• Read Lidar Laser Scan Data over ROS from Raspberry Pi
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware to read and receive a 2-D lidar scan data of an indoor environment from a ROS network using the Raspberry Pi hardware board.
• Track Object Using ROS and Simulink on Raspberry Pi
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware, ROS Toolbox, and a Raspberry Pi hardware board to track a green colored object. This example also shows how to use the Publish and Subscribe blocks to establish communication between the ROS node deployed on the Raspberry Pi hardware board and the ROS node in Simulink (host computer).

イメージ処理とビデオ処理を使用した適用例

• Customize Color Within Video Using Raspberry Pi
  This example shows you how to replace a particular color in a live video stream with an image on Raspberry Pi® hardware by using a MATLAB Function block.
• Detect Boundaries of Objects Within Video Using Raspberry Pi
  This example shows you how to identify the boundaries of objects in a live video stream on Raspberry Pi® hardware by using a MATLAB Function block with the Simulink® Support Package for Raspberry Pi Hardware. The process of identifying boundaries of objects is known as edge detection. This example implements the Sobel edge detection algorithm to identify the boundaries of the objects.
• Implement Image Inversion Algorithm Using Raspberry Pi
  This example shows how to use the V4L2 Video Capture and the SDL Video Display blocks from the Raspberry Pi® block library to implement an image inversion algorithm with a Simulink® model, and to run the model on Raspberry Pi hardware.
• Implement Connected I/O on Raspberry Pi Hardware and Publish Data to WebSocket Server
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to develop an image processing system on Raspberry Pi board using a camera in the connected I/O mode. The example also shows you how to publish the output on a web browser and on a SDL video display screen.
• Video Mosaicking Using Raspberry Pi Pan Tilt HAT
  This example shows how to use the Pan Tilt HAT block from Simulink® Support Package for Raspberry Pi® Hardware to create a mosaic from a video sequence. Video mosaicking is the process of stitching video frames together to form a comprehensive view of a scene. The resulting mosaic image is a compact representation of the video data. This technique is often used in video compression and surveillance applications.
• Detect and Track Face Using Raspberry Pi Pan Tilt HAT
  This example shows how to use the Pan Tilt HAT block from Simulink® Support Package for Raspberry Pi® Hardware to detect and track a face in a video frame. The example also tracks a face when a person tilts their head either left or right or moves toward or away from the camera. If the face is not visible or goes out of focus, the model tries to reacquire the face and then tracks the face. The model in this example can detect and track only one face at a time. You can also enable the proportional-integral-derivative (PID) controller to achieve a smooth motion of the pan and tilt hardware module for tracking the face.
• Stream Video Over Network Using Raspberry Pi RTSP Video Stream Transmit Block
  This example shows how to use the RTSP Video Stream Transmit block from the Simulink Support Package for Raspberry Pi Hardware to stream a live video over a network using real-time streaming protocol (RTSP).

オーディオ処理を使用した適用例

• Implement Parametric Audio Equalizer Using Raspberry Pi
  This example shows how to use ALSA Audio Playback block from the Raspberry Pi® block library to implement a parametric audio equalizer algorithm with a Simulink® model and to run the model on Raspberry Pi hardware.
• Spatialize Monaural Audio into 5.1 Channel Surround Sound Using Raspberry Pi
  This example shows you how to spatialize a monaural audio signal into a 5.1 channel surround sound on Raspberry Pi® hardware by using a MATLAB Function block with the Simulink® Support Package for Raspberry Pi Hardware.
• Shift Pitch of Audio Signal Using Raspberry Pi
  This example shows you how to shift the pitch of an audio signal on Raspberry Pi® hardware by using a MATLAB Function block with the Simulink® Support Package for Raspberry Pi Hardware.
• Play High-Quality Audio from Raspberry Pi Using I2S-Based DAC
  Enable I2S drivers to output high-quality audio from Raspberry Pi using DAC.
• Implement Bandpass Filter on Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to design a bandpass filter using DSP System Toolbox™.
• Implement Adaptive Filter for Noise Cancellation Using Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to implement an adaptive filter for noise cancellation using DSP System Toolbox™.
• Estimate Direction of Arrival with Linear Array of Microphones Using Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to estimate the Direction of Arrival (DOA) of a sound source using multiple microphone pairs within a linear array using the Raspberry Pi hardware board. A servo motor is used to point towards the sound source based on the estimated DOA.

携帯電話とタブレットを使用した適用例

• Build Surveillance Camera Using Android and Raspberry Pi
  This example shows how to use Raspberry Pi® hardware and an Android® device to build a surveillance camera.
• Control Status of LED on Raspberry Pi from Android Device
  This example shows you how to control Raspberry Pi® LED from an Android® device.

通信ブロックを使用した適用例

• Transmit and Receive Data Using Raspberry Pi CAN Blocks
  This example shows to use Simulink® Support Package for Raspberry Pi® Hardware to transmit and receive data from the CAN network using the specified CAN device.
• Monitor Engine RPM Using Raspberry Pi CAN Blocks
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware to monitor vehicle engine RPM and read the data on a web browser.
• MODBUS TCP/IP Communication Between Client and Server Devices Using Raspberry Pi Hardware
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to implement MODBUS® TCP/IP communication between MODBUS client and server devices. It also shows how to communicate between the two devices in four modes of operation, Client Read, Client Write, Server Read, and Server Write.
• Communicate Data Between Raspberry Pi and Sense HAT Using NNG Blocks
  This example shows how to use the NNG Send and NNG Receive blocks from the Simulink® Support Package for Raspberry Pi™ Hardware to establish communication between the Raspberry Pi hardware and Sense HAT using the nanomsg next generation (NNG) library.
• Read and Write to ThingSpeak Channel Using Raspberry Pi HTTP Client Block
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware to read and write data to a field in a ThingSpeak™ channel. In this example, you read data from the GPIO pin of the Raspberry Pi hardware and write it to a field in a ThingSpeak channel.

IoT を使用した適用例

• Publish and Subscribe to Messages on ThingSpeak Using MQTT Blocks on Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware 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 の基礎 (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).
• Control LED Status Using ThingSpeak TalkBack on Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to fetch and execute commands from a ThingSpeak™ TalkBack queue and use them to change the status of an LED onboard a Raspberry Pi hardware board.

深層学習と機械学習のアルゴリズムを使用した適用例

• Classify Objects Using Deep Learning Algorithm on Raspberry Pi Hardware
  This example shows how to use the Simulink® Support Package for Raspberry Pi® 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.
• Recognize Handwritten Digits Zero to Nine Using MNIST Data Set on Raspberry Pi Hardware
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to recognize images of handwritten digits from zero to nine. In this example, a web camera interfaced with a Raspberry Pi hardware board is used to capture images of the handwritten numbers. The algorithm recognizes the digits and then outputs a label for the digit along with its prediction probability.
• Perform Predictive Maintenance for Rotating Device Using Machine Learning Algorithm on Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to predict and monitor the health of a rotating device using a machine learning algorithm. You can use this example for predictive maintenance of any rotating device or piece of equipment so that you can fix them before they fail.

DSP System Toolbox を使用した適用例

• Verify FIR Filter on Raspberry Pi Hardware
  This example shows how to use the Code Replacement Library (CRL) for Raspberry Pi® hardware with DSP blocks. The model uses the FIR filter block to filter two sine waves of different frequencies.
• Support NE10 Library C Code Generation of dsp.FIRFilter in MATLAB Function Block
  This example shows how to use the Code Replacement Library (CRL) for Raspberry Pi® hardware with DSP System object™. The model uses a MATLAB Function that contains a dsp.FIRFilter System object to filter two sine waves of different frequencies.
• Supported ARM Cortex-A Processors for Raspberry Pi Hardware
  ARM^® Cortex^®-A processors supported by Raspberry Pi boards.

Simulink と Simulink Online を使用したロボティクスへの適用例

• Get Started with Sensors for Robotics Applications Using Raspberry Pi and Simulink Online
  This example shows how to use Simulink® Support Package for Raspberry Pi® Hardware and a Raspberry Pi hardware board to get started with the driver blocks for commonly used robotics sensors.
• Get Started with Motor Drives for Robotics Applications Using Raspberry Pi and Simulink
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware and a Raspberry Pi hardware board to drive motors.
• Detect Stop Signal Traffic Sign Using Raspberry Pi and Simulink
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to detect a stop signal traffic sign. The example uses a cascade object detector to detect a stop sign using the Viola-Jones algorithm.
• Develop Path-Following Robot Using Raspberry Pi and Simulink
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to develop a path-following robot.
• Develop Robot Navigation System Using Raspberry Pi and Simulink
  This example illustrates how to use the Simulink® Support Package for Raspberry Pi® Hardware to develop a robot navigation system.
• Develop Obstacle Detection Robot Using ToF Sensor with Raspberry Pi
  This example shows how to use the Simulink® Support Package for Raspberry Pi® Hardware to interface a VL53L0X Time of Flight (ToF) sensor with the Raspberry Pi hardware to develop an obstacle detection robot.