Keywords

wilderness search and rescue, UAVs, unmanned aerial vehicles, path planning, probability dsitribution map

Abstract

In the priority search phase of Wilderness Search and Rescue, a probability distribution map is created. Areas with higher probabilities are searched first in order to find the missing person in the shortest expected time. When using a UAV to support search, the onboard video camera should cover as much of the important areas as possible within a set time. We explore several algorithms (with and without set destination) and describe some novel techniques in solving this problem and compare their performances against typical WiSAR scenarios. This problem is NP-hard, but our algorithms yield high quality solutions that approximate the optimal solution, making efficient use of the limited UAV flying time.

Original Publication Citation

L. Lin and M. A. Goodrich. UAV Intelligent Path Planning for Wilderness Search and Rescue, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. Oct, 29 St. Louis, Missouri, USA.

Document Type

Peer-Reviewed Article

Publication Date

2009-10-01

Permanent URL

http://hdl.lib.byu.edu/1877/2379

Publisher

IEEE

Language

English

College

Physical and Mathematical Sciences

Department

Computer Science

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