probabilistic search, UAV, unmanned aircraft
Ground breaking concepts in optimal search theory were developed during World War II by the U.S. Navy. These concepts use an assumed detection model to calculate a detection probability rate and an optimal search allocation. Although this theory is useful in determining when and where search effort should be applied, it offers little guidance for the planning of search paths. This paper explains how search theory can be applied to path planning for an SUAV with a fixed CCD camera. Three search strategies are developed: greedy search, contour search, and composite search. In addition, the concepts of search efficiency and search completeness are offered as metrics for search effectiveness. Simulation results comparing the effectiveness of the strategies are presented.
Original Publication Citation
Steven Hansen, Timothy McLain, and Michael Goodrich. "Probabilistic Searching Using a Small Unmanned Aerial Vehicle", AIAA Infotech@Aerospace 2007 Conference and Exhibit, Infotech@Aerospace Conferences. http://dx.doi.org/10.2514/6.2007-2740
BYU ScholarsArchive Citation
Hansen, Steven R.; McLain, Timothy W.; and Goodrich, Michael A., "Probabilistic Searching Using a Small Unmanned Aerial Vehicle" (2007). All Faculty Publications. 1509.
Ira A. Fulton College of Engineering and Technology
Hansen, S. McLain, T. and Goodrich, M. Probabilistic Searching Using a Small Unmanned Aerial Vehicle, Proceedings of the 2007 AIAA Infotech@Aerospace Conference, AIAA 2007-2740, May 2007, Rohnert Park, CA. doi: 10.2514/6.2007-2740
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