Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/104246
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Type: Journal article
Title: Probabilistic multi-hypothesis tracker for multiple platform path planning
Author: Cheung, B.
Davey, S.
Gray, D.
Citation: IET Radar, Sonar and Navigation, 2015; 9(3):255-265
Publisher: Institution of Engineering and Technology
Issue Date: 2015
ISSN: 1751-8784
1751-8792
Statement of
Responsibility: 
Brian Cheung, Samuel Davey, Douglas Gray
Abstract: This study considers the problem of automatically coordinating multiple platforms to explore an unknown environment. The goal is a planning algorithm that provides a path for each platform in such a way that the collection of platforms cooperatively sense the environment in a globally efficient manner. The environment is described by a spatially non-homogeneous priority function. The method samples this function to produce a discrete collection of locales that the platforms use as waypoints. The key feature of the method is to treat the assignment of locales to platforms as a target tracking problem and to use the probabilistic multi-hypothesis tracker (PMHT) as a method of performing multi-platform batch data association. This paper introduces the PMHT path planner (PMHT-pp) and compares this algorithm as a method of performing multiple platform batch data association with the Genetic Algorithm to solve the modified multi-travelling salesman problem.
Keywords: Travelling salesman problems; genetic algorithms; path planning; probability; sensor fusion; target tracking
Rights: © Commonwealth of Australia 2015
RMID: 0030024781
DOI: 10.1049/iet-rsn.2014.0089
Published version: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7054601&filter=AND(p_IS_Number:7054575)
Appears in Collections:Electrical and Electronic Engineering publications

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