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Autonomous Driving Model: Lane Detection and Visual Odometry for a Robotic Autonomous Vehicle
Author/Artist
Kendrick, Zachary
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Format
Senior thesis
Language
English
Availability
Available Online
Full text:
DataSpace
Details
Advisor(s)
Cuff, Paul W.
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Department
Princeton University. Department of Electrical Engineering
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Certificate
Princeton University. Program in Applications of Computing
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Class year
2017
Summary note
The goal of this thesis is to demonstrate that an autonomous vehicle can effectively navigate a roadway using only a single low cost RGB camera. More specifically, the project studies how to develop a lane detection and visual odometry system for autonomous driving. Using a scaled down robotic model of a car to test the algorithms, the thesis first models a lane detection algorithm that allows the robotic car to follow roadways using similar methods that a full scale car would use to track lane markings on a paved roadway. Building off of the lane detection algorithm, this project develops a monocular ORB visual odometry system for the robot car which allows it to build a map of the roadway on which it is traveling.
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