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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Bourgault, F., Furukawa, T., & Durrant-Whyte, H. F. (2006). Optimal search for a lost target in a Bayesian world. Springer Tracts in Advanced Robotics, 24, 209–222. https://doi.org/10.1007/10991459_21
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