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.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-1119 |
| Date | 12 March 2004 |
| Creators | Hintze, Joshua Martin |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | http://lib.byu.edu/about/copyright/ |
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