2020FallTeam1

Team Members

Electrical Engineers

Benjamin Crawford

Heather Huntley

Joshua Orozco

Mechanical Engineers

Peggy Tran

Project Overview

Initially the goal of our project was to design an autonomous vehicle that would utilize DonkeyAI framework, open CV, and sensors to detect and gather tennis balls in one area to facilitate collecting them after each set. Due to COVID-19, the scope of our project was pivoted to create a ROS package that enables the RoboCar to use images taken through its external camera to be processed through a mask and proportional-integral-derivative tuning in order to read the yellow lines on the racetrack and drive autonomously.

Hardware

Mechanical Design

Camera Mount

Base Plate

This base plate was printed on .25 inch acrylic and was used to hold all electrical components of the RoboCar.

Electronic Components

Jetson Nano Developer Kit

Adafruit PCA9685

16bit PWM controller

USB webcam

High power LEDs

11.1V 3S LiPo battery

Battery voltage sensor

433MHz remote relay

12V-5V DC-DC voltage converter

The car our team used is built around a Traxxas Ford Fiesta chassis containing a DC motor, electronic speed controller and servo motor. The following diagram shows how all of the electronics are wired.

Software

We set up a GitHub repository where the code used by the vehicle is stored. The repository contains an ROS package which is designed to be used with our car. The following diagram displays the overall structure of the out ROS package, Autonomous_ROS_Racer.

Milestones

DonkeyCar

Using the donkeycar framework and the UCSD GPU cluster to speed up the behavioral modeling process we were able to do five autonomous laps on an outdoor track. As you can see in the video below:
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ROS Package

With the ROS package that we developed we completed five laps (with a little help) on the track in the Warren tents. Here is a video of that:
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Acknowledgements

We would like to thank Professors Jack Silberman and Mauricio de Oliveira for their help throughout the quarter and consistent work in keeping the course engaging and relevant throughout the difficulties imposed by the COVID pandemic. We would also like to recognize the hard work put in by the TA's Haoru and Leeor.