2020WinterTeam7
Contents
Project Overview
Our goal was to provide our car with particular GPS coordinates, have the car navigate to the destination coordinates by using GPS and RTK2 corrections to achieve centimeter accuracy. We utilized Potential Functions and Gradient descent algorithm to avoid obstacles and find the path through objects.
Main objectives of adaptive cruise control are:
1. GPS-RTK Navigation from source to the assigned destination
2. Connecting the two C099-F9P GPS-RTK2 modules using Odin (wifi)
3. Obstacle avoidance
Team Members
Chanyang Yim – Mechanical and Aerospace Engineering Department
Jiuqi Wang – Mechanical and Aerospace Engineering Department
Omid Hasanli – Electrical and Computer Engineering Department
Design and Assembly of Donkey
Plate and Camera Mount Design
Autonomous Driving using gradient descent
The General Idea
To build potential fields, so that the point that represents the robot is attracted by the goal and repelled by the obstacle region. The robot moves to a lower energy configuration and energy is minimized by following the negative gradient of the potential energy function.
Artificial Potential Field Methods
The Attractive Potential
– Uatt is the “attractive” potential --- move to the goal
The Repulsive Potential
– Urep is the “repulsive” potential --- avoid obstacles
Total Potential Function
– Uatt is the “attractive” potential --- move to the goal – Urep is the “repulsive” potential --- avoid obstacles
