Date of Award

1-1-2017

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering

First Advisor

Kyoung-Dae Kim, Ph.D.

Second Advisor

Margareta Stefanovic

Third Advisor

Vijaya Narapareddy

Keywords

Autonomous vehicles, Constrained optimization, Non-linear optimization, Optimal control, Optimal path generation, Trajectory generation

Abstract

This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal path through a track. Also, when using a path to guide an autonomous vehicle, paths represented in the continuous domain can allow for better tracking and control than discrete counterparts. As autonomous systems become more integral to our society, increased computational efficiency, tracking, and control are important areas of improvement.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Tyler Friedl

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

116 p.

Discipline

Electrical engineering, Robotics

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