Title page for ETD etd-12162008-152233

Type of Document Master's Thesis
Author Dalton, Aaron James
Author's Email Address aadalton@vt.edu
URN etd-12162008-152233
Title Autonomous Vehicle Path Planning with Remote Sensing Data
Degree Master of Science
Department Geography
Advisory Committee
Advisor Name Title
Carstensen, Laurence William Jr. Committee Chair
Campbell, James B. Jr. Committee Member
Wicks, Alfred L. Committee Member
  • path planning
  • autonomous vehicles
  • remote sensing
Date of Defense 2008-12-02
Availability unrestricted
Long range path planning for an autonomous ground vehicle with minimal a-priori data is still very much an open problem. Previous research has demonstrated that least cost paths generated from aerial LIDAR and GIS data could play a role in automatically determining suitable routes over otherwise unknown terrain. However, most of this research has been theoretical. Consequently, there is very little literature the effectiveness of these techniques in plotting paths of an actual autonomous vehicle. This research aims to develop an algorithm for using aerial LIDAR and imagery to plan paths for a full size autonomous car. Methods of identifying obstacles and potential roadways from the aerial LIDAR and imagery are reviewed. A scheme for integrating the path planning algorithms into the autonomous vehicle existing systems was developed and eight paths were generated and driven by an autonomous vehicle. The paths were then analyzed for their drivability and the model itself was validated against the vehicle measurements. The methods described were found to be suitable for generating paths both on and off road.
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