Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
Full metadata record
|dc.identifier.citation||IET Radar, Sonar and Navigation , 2015; 9(3):255-265||-|
|dc.description.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.||-|
|dc.description.statementofresponsibility||Brian Cheung, Samuel Davey, Douglas Gray||-|
|dc.publisher||Institution of Engineering and Technology||-|
|dc.rights||© Commonwealth of Australia 2015||-|
|dc.subject||Travelling salesman problems; genetic algorithms; path planning; probability; sensor fusion; target tracking||-|
|dc.title||Probabilistic multi-hypothesis tracker for multiple platform path planning||-|
|Appears in Collections:||Aurora harvest 3|
Electrical and Electronic Engineering publications
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.