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|Title:||Probabilistic multi-hypothesis tracker for multiple platform path planning|
|Citation:||IET Radar, Sonar and Navigation, 2015; 9(3):255-265|
|Publisher:||Institution of Engineering and Technology|
|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|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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