Difference between revisions of "2022WinterTeam6"
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== Code/Github ==
== PID Algorithm ==
== PID Algorithm ==
Revision as of 06:02, 19 March 2022
Team 6: DKar
- Aksharan Saravanan, ECE
- Hieu Luu, DSC
- Katada Siraj, MAE
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.
- 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
~~image (original gantt)~~ ~~image (updated gantt)~~
~~image (robot hardware)~~
~~images (for cad models and lasercut board)~~ (and maybe short description?)
~~image (wiring schematic)~~
- Intel RealSense RGBD Camera
- Mini Laser
- Micro Servo
~~images (for each component)
~~video (of EMO)~~
Explanation/How We Did It
ROS Software Design
Github Link: Project Code
Custom ROS Node Link: ROS2 Node
Final Project Presentation
Weekly Update Presentations
- 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
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.
Thanks to: Professor Silberman, Dominic, Ivan, Professor De Oliveira, as well as the other teams.