Abstract

Landing an Unmanned Aerial Vehicle (UAV) is a non-trivial problem. Removing the ability to cooperate with the landing site further increases the complexity. This thesis develops a multi-stage process that allows a UAV to locate the safest landing site, and then land without a georeference. Machine vision is the vehicle sensor used to locate potential landing hazards and generate an estimated UAV position. A description of the algorithms, along with validation results, are presented. The thesis shows that software-simulated landing performs adequately, and that future hardware integration looks promising.

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2004-03-12

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd359

Keywords

UAV, unmanned, aerial, vehicle, rotorcraft, rotary, landing, non-cooperative, autonomous

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