Difference between revisions of "2020WinterTeam7"

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(Autonomous Driving using gradient descent)
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== Autonomous Driving using gradient descent==
 
== Autonomous Driving using gradient descent==
  
<h4>Indoor</h4>
+
<h4>The General Idea</h4>
  
<h4>Outdoor</h4>
+
<h4>Artificial Potential Field Methods</h4>
 +
 
 +
<h5>The Attractive Potential<h5>
 +
 
 +
<h5>The Repulsive Potential<h5>
 +
 
 +
<h5>Total Potential Function<h5>
 +
 
 +
<h4> Gradient Descent <h4>
  
 
==Challenges==
 
==Challenges==

Revision as of 10:22, 20 March 2020


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

Artificial Potential Field Methods

The Attractive Potential<h5> <h5>The Repulsive Potential<h5> <h5>Total Potential Function<h5>

Gradient Descent <h4>

Challenges

Conclusion

==Project Links==