2021FallTeam8

From MAE/ECE 148 - Introduction to Autonomous Vehicles
Jump to navigation Jump to search

Team Members

  • Colin Riccio - Mechanical Engineering
  • Brian Pack - Mechanical Engineering
  • Carolin Lehmacher - Electrical Engineering

Robot

Robocar - Project

The picture on the right shows our Robocar and part of the wiring for our used project.

Robocar for our Project


Mechanical Design

Camera Mount

The mount system was 3d printed and had 3 parts: a camera backplate, a stand and a lidar mount. The Lidar mount ties into the front standoffs and the stand attaches to the electronics plate.

The camera mount has a pivot joint to allow for repositioning the camera angle. This proved to be initially helpful to set an optimal angle, but we ran into issues where if the mount was bumped it would lead to failures with our DonkeyCar models. It might be a good idea to first have a variable angle mount, find the best setting for the camera, and then create a static mount to use for training.

Electronic Plate The plate was designed with a full array of mounting holes to facilitate the attachment of parts anywhere on the plate. It was laser cut from 1/8th inch acrylic.

Electrical Design

Components

  • Jetson Nano 2GB
  • Battery
  • USB Camera
  • Servo
  • Xerun 360
  • Anti spark switch
  • 12V to 5V Converter
  • Flipsky mini


Wiring

The following picture shows the wiring of the robocar used for the project.

wiring_8.jpg

Autonomous Lab using ROS

The following video shows a short sequence of the autonomous labs of Team 8 using ROS.

File:ROS2 Lab.mov

Project Overview

Speed Sign Recognition

For this project, we are using ROS, motor speed feedback and DNN image recognition to dynamically change the driving speed of the car in response to speed limit signs.

What we did:

  • started with getting the docker running
  • calibrated the car for the speed control
  • researched encoder theory and what we need for controlling the speed of the car
  • reading output from the hall sensors
  • setting a speed limit
  • learning OpenCV
  • printed out speed signs
  • collected data for the image recognition
  • recognizing the different speed signs
  • integrating speed control and sign recognition into ROS
  • testing