2022WinterTeam2

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

Bold text

Team Members

ECE

  • Roger Kim

RogerKim.jpg

  • Bishwajit Roy

2000 (2).jpg]

MAE

  • Tara Len
  • Cameron Yenche

CameronYenche.png

Team 2 Car

Isometric View

CarISO.jpg

Side View

1000 (3).jpg

Project Overview

The purpose of this project is to replicate autonomous interaction with traffic signals. Taking cues from industry leadership, this will be done using camera-based computer vision navigation tool.

Mechanical Design

Baseplate

Image.jpg

The baseplate has three slots running down its middle section that are 34.29 in long and three slots on one side that are 12.70 in long. All of these slots are 0.625 inches apart from each other and they all have a width of 0.32 in, which allows M3 screws to be inserted inside those slots. There is a wider slot located on the opposite side of the three short slots that allows more space for wiring and hardware.

Camera Mount

CameraMountT2.png

The camera mount consisted of a simple joint with spacing for the camera wiring to run through the mount as well as spaced M3 holes for mounting to both the camera and the baseplate. The component was printed from PETG filament using a standard Fused Deposition Modeling (FDM) 3D printer.

Jetson Nano Protective Case

JetsonNanoCase.png

The Jetson Nano case sourced from an open-source repository and serves the purpose of protecting and securing the Jetson Nano from damage, should a crash occur (which it did). The component was printed from PETG filament using a standard Fused Deposition Modeling (FDM) 3D printer.

Electrical Design

Wiring Schematic

WI22 Team2 Schematic.png


Programming Design

Color Filter Flowchart (OpenCV)

WI22 Team2 OpenCV Flowchart.png

The computer vision script works by converting each frame into HSV space, forming a mask for each target color (red, yellow, and green), and applying the hough circle transform to each masked image. If a circle of the proper size and color range is detected, the script will output the corresponding traffic signal logic to be used by ROS2 for directing the car.

StopLightGif.gif

The GIF above is a visualization of the computer vision script detection.

ROS2 Flow Chart

ROS2 Flow Chart.png

Repositories
ECE/MAE 148 WI22 Team2 GitHub
ECE/MAE 148 WI22 Team2 GitLab (ROS2 Integration)