ECE 4180 Final Project - Fall 2019

Team Members

• Aldo Rogliero
• Caitlin Choate
• David Fernandez

Project Description

The project involves a robot that can be controlled in two modes:

• Manual mode
  • Using the BlueFruit app
• Autonomous mode
  • Using the Pi Camera to detect images and react to them

Software Overview

The The Pi listens for an “autonomous mode” signal and sends back output from the SVM to the Mbed. Mbed handles the bluetooth commands and controls the mode detected, as well as robot actions

Mbed:

• Main loop controls commands received from Bluetooth and responds accordingly.
• When in autonomous mode, it listens to the Pi for commands.
• Reacts to a Bluetooth or Pi signal depending on the mode.

mbed code:

https://os.mbed.com/teams/Semi-Autonomous-Robot/code/Semi-Autonomous-Robot-ECE-4180//file/e0dbd261724a/mbed/

Raspberry Pi:

• Implements the Support Vector Machine (SVM) that allows for image detection
• Sends commands to the Mbed signaling which action to take

Raspberry Pi code:

https://os.mbed.com/teams/Semi-Autonomous-Robot/code/Semi-Autonomous-Robot-ECE-4180//file/183a8efd562a/pi/

Hardware Overview

Below is a diagram showing the pin connections and layout of the hardware components

Demo