Abstract
This paper presents a Bayesian approach to the problem of searching for a single lost target by a single autonomous sensor platform. The target may be static or mobile but not evading. Two candidate utility functions for the control solution are highlighted, namely the Mean Time to Detection, and the Cumulative Probability of Detection. The framework is implemented for an airborne vehicle looking for both a stationary and a drifting target at sea. Simulation results for different control solutions are investigated and compared to demonstrate the effectiveness of the method.
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© 2006 Springer-Verlag Berlin Heidelberg
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Bourgault, F., Furukawa, T., Durrant-Whyte, H.F. (2006). Optimal Search for a Lost Target in a Bayesian World. In: Yuta, S., Asama, H., Prassler, E., Tsubouchi, T., Thrun, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10991459_21
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DOI: https://doi.org/10.1007/10991459_21
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32801-8
Online ISBN: 978-3-540-32854-4
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