Optimal Search for a Lost Target in a Bayesian World

  • Frédéric Bourgault
  • Tomonari Furukawa
  • Hugh F. Durrant-Whyte
Part 5 - Mapping and Tracking
Part of the Springer Tracts in Advanced Robotics book series (volume 24)

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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Authors and Affiliations

  • Frédéric Bourgault
    • 1
  • Tomonari Furukawa
    • 2
  • Hugh F. Durrant-Whyte
    • 1
  1. 1.ARC Centre of Excellence for Autonomous Systems (CAS) Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006Australia
  2. 2.ARC Centre of Excellence for Autonomous Systems (CAS), School of Mechanical and Manuf. Engineering, The University of New South Wales, Sydney, NSW 2052Australia

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