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Target Estimate PDF-Based Optimal Path Planning Algorithm With Application to UAV Systems

[+] Author Affiliations
Jared G. Wood, Benjamin Kehoe, J. Karl Hedrick

University of California, Berkeley, Berkeley, CA

Paper No. DSCC2010-4262, pp. 749-756; 8 pages
  • ASME 2010 Dynamic Systems and Control Conference
  • ASME 2010 Dynamic Systems and Control Conference, Volume 2
  • Cambridge, Massachusetts, USA, September 12–15, 2010
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4418-2 | eISBN: 978-0-7918-3884-6
  • Copyright © 2010 by ASME


Companies are starting to explore investing in UAV systems that come with standard autopilot trackers. There is a need for general cooperative local path planning algorithms that function with these types of systems. We have recently finished a project in which algorithms for autonomously searching for, detecting, and tracking ground targets was developed for a fixed-wing UAV with a visual spectrum gimballed camera. A set of scenarios are identified in which finite horizon path optimization results in a non-optimal ineffective path. For each of these scenarios, an appropriate path optimization problem is defined to replace finite horizon optimization. An algorithm is presented that determines which path optimization should be performed given a UAV state and target estimate probability distribution. The algorithm was implemented and thoroughly tested in flight experiments. The experimental work was successful and gave insight into what is required for a path planning algorithm to robustly work with standard waypoint tracking UAV systems. This paper presents the algorithm that was developed, theory supporting the algorithm, and experimental results.

Copyright © 2010 by ASME



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