# object-tracking-using-ros-and-simulink-on-raspberry-pi

**Repository Path**: code_lixin/object-tracking-using-ros-and-simulink-on-raspberry-pi

## Basic Information

- **Project Name**: object-tracking-using-ros-and-simulink-on-raspberry-pi
- **Description**: The example showcases deployment of a object tracking algorithm using ROS on the Raspberry Pi. The example intends to show the functionality of deploying ROS nodes on Pi and monitoring the values on a system on the same network.
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-07-03
- **Last Updated**: 2024-11-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Object Tracking using ROS and Simulink on Raspberry Pi

Copyright 2020 The MathWorks Inc.

## Introduction
This repository contains resources for deploying a ROS node on Raspberry Pi hardware using Simulink showcasing an object tracking example.

## Folder Structure
The repository has two examples which are located in two different folders:
1. ***PublishPi***: Deploy a standalone ROS node with vision and control algorithms and validate it from another Simulink model for visualization.
2. ***PublishSubscribePi***: Publish and Subscribe between a ROS node in Simulink and a standalone ROS node deployed onto Raspberry Pi.

The Raspberry Pi model has to be deployed on the hardware, whereas the Desktop model is to be run on the system. 

## Setup
1. Clone the repository.
2. Open MATLAB and navigate to *PublishPi* or *PublishSubscribePi* folder.
3. Open the Raspberry Pi model. Deploy the model on the hardware using Robot -> Build & Run. Installation of Raspberry Pi Support from Simulink would be necessary: 
https://www.mathworks.com/hardware-support/raspberry-pi-simulink.html
4. Open the Desktop model and **run** the model.

For any queries, contact the authors at roboticsarena@mathworks.com