Abstract
This paper presents a technique for dynamically determining search spaces in order to enable sensor exploration during autonomous search and tracking (SAT) missions. In particular, marine search and rescue scenarios are considered, highlighting the need for exploration during SAT. A comprehensive method which is independent of search space representation is introduced, based on exploration frontiers and reachable set analysis. The advantage of the technique is that recursive Bayesian estimation can be performed indefinitely, without loss of information. Numerical results involving multiple search vehicles and multiple targets demonstrate the efficacy of the approach for coordinated SAT. These examples also highlight the added benefit for human mission planners resulting from the technique’s simplification of the search space allocation task.
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Lavis, B., Furukawa, T. (2007). Dynamic Search Spaces for Coordinated Autonomous Marine Search and Tracking. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_103
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DOI: https://doi.org/10.1007/978-3-540-73325-6_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
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