Title page for ETD etd-08192008-231631

Type of Document Master's Thesis
Author Klomparens, Dylan
Author's Email Address dylan.klomparens@gmail.com
URN etd-08192008-231631
Title Automated Landing Site Evaluation for Semi-Autonomous Unmanned Aerial Vehicles
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Abbott, A. Lynn Committee Chair
Broadwater, Robert P. Committee Member
Kochersberger, Kevin Bruce Committee Member
Plassmann, Paul E. Committee Member
  • Obstacle Detection
  • Supervisory Control
  • UAV
  • Landing Site Evaluation
  • Stereo Vision
  • User Performance Evaluation
Date of Defense 2008-08-20
Availability unrestricted
A system is described for identifying obstacle-free landing sites for a vertical-takeoff-and-landing (VTOL) semi-autonomous unmanned aerial vehicle (UAV) from point cloud data obtained from a stereo vision system. The relatively inexpensive, commercially available Bumblebee stereo vision camera was selected for this study. A “point cloud viewer” computer program was written to analyze point cloud data obtained from 2D images transmitted from the UAV to a remote ground station. The program divides the point cloud data into segments, identifies the best-fit plane through the data for each segment, and performs an independent analysis on each segment to assess the feasibility of landing in that area. The program also rapidly presents the stereo vision information and analysis to the remote mission supervisor who can make quick, reliable decisions about where to safely land the UAV. The features of the program and the methods used to identify suitable landing sites are presented in this thesis. Also presented are the results of a user study that compares the abilities of humans and computer-supported point cloud analysis in certain aspects of landing site assessment. The study demonstrates that the computer-supported evaluation of potential landing sites provides an immense benefit to the UAV supervisor.
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