Dynamic search spaces for coordinated autonomous marine search and tracking

Authors:
Benjamin Lavis;Tomonari Furukawa
Affiliations:
ARC Centre of Excellence for Autonomous Systems, School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, Australia;ARC Centre of Excellence for Autonomous Systems, School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, Australia
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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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.