2022WinterTeam6

Team 6: DKar

~~donkey in a car~~

Team Members

• Aksharan Saravanan, ECE
• Hieu Luu, DSC
• Katada Siraj, MAE

~~team pic~~

Project Overview

A robot that acts as an aimbot, in that it follows a target and dynamically adjusts a laser pointing at that target. The robot should use OpenCV to detect the target and ROS to guide steering and throttle based on the target position and distance.

Goals:

• Have the car be able to autonomously follow a target (e.g. a poster board)
• Modify the car to fit a laser pointer that aims at the target

• (Nice-to-have)Recognize targets of different colors and adjust the following distance.
  • Alternative: Use depth data from intel to implement throttle control

Gantt Charts

~~image (original gantt)~~ ~~image (updated gantt)~~

Robot setup

Hardware Setup

~~image (robot hardware)~~

CAD/Mechanical Designs

~~images (for cad models and lasercut board)~~ (and maybe short description?)

Wiring

~~image (wiring schematic)~~

Special Components

• Intel RealSense RGBD Camera
• Mini Laser
• Micro Servo

~~images (for each component)

Emergency Stop

~~video (of EMO)~~

Challenges

• Determining how to integrate custom ROS code within the Docker Container and getting the Nodes to communicate
• Integrating the Intel RealSense Camera
• Issue of possible “voltage spike” to the ESC causing full throttle in some cases
• Connecting ideas of OpenCV image detection and doing data processing to publish to ROS topics
• Components including the Jetson, PWM, and switch burned out so had to get new parts

Future Developments

Send reverse throttle controls.

• This would enable our car to be more robust in maintaining a following distance because it would be able to correct itself when overshooting. We weren’t able to implement this because we didn’t address it soon enough and with the little time we had, we didn’t want to risk messing around with the ESC.

Recognize different colors and dynamically adjust following distance.

• This would allow the car to be more responsive to the environment and more robust when following a target. We weren’t able to implement this as we didn’t get enough time and didn’t get to start.

Acknowledgements

Thanks to: Professor Silberman Dominic Ivan Professor De Oliveira as well as the other teams.