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Proceedings Paper

A UAV routing and sensor control optimization algorithm for target search
Author(s): Gaemus E. Collins; James R. Riehl; Philip S. Vegdahl
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Paper Abstract

An important problem in unmanned air vehicle (UAV) and UAV-mounted sensor control is the target search problem: locating target(s) in minimum time. Current methods solve the optimization of UAV routing control and sensor management independently. While this decoupled approach makes the target search problem computationally tractable, it is suboptimal. In this paper, we explore the target search and classification problems by formulating and solving a joint UAV routing and sensor control optimization problem. The routing problem is solved on a graph using receding horizon optimal control. The graph is dynamically adjusted based on the target probability distribution function (PDF). The objective function for the routing optimization is the solution of a sensor control optimization problem. An optimal sensor schedule (in the sense of maximizing the viewed target probability mass) is constructed for each candidate flight path in the routing control problem. The PDF of the target state is represented with a particle filter and an "occupancy map" for any undiscovered targets. The tradeoff between searching for undiscovered targets and locating tracks is handled automatically and dynamically by the use of an appropriate objective function. In particular, the objective function is based on the expected amount of target probability mass to be viewed.

Paper Details

Date Published: 8 May 2007
PDF: 13 pages
Proc. SPIE 6561, Unmanned Systems Technology IX, 65610D (8 May 2007); doi: 10.1117/12.718888
Show Author Affiliations
Gaemus E. Collins, Toyon Research Corp. (United States)
James R. Riehl, Univ. of California, Santa Barbara (United States)
Philip S. Vegdahl, Toyon Research Corp. (United States)

Published in SPIE Proceedings Vol. 6561:
Unmanned Systems Technology IX
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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