- Roger Kim
- Bishwajit Roy
- Tara Len
- Cameron Yenche
Team 2 Car
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.
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.
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
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.
Color Filter Flowchart (OpenCV)
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.
The GIF above is a visualization of the computer vision script detection.
ROS2 Flow Chart'