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Distributed multi-vehicle task assignment in a time-invariant drift field with obstacles

Bai, X., Yan, W., Cao, M. & Xue, D., 26-Nov-2019, In : IET Control Theory and Applications. 13, 17, p. 2886-2893 8 p.

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  • Distributed multi-vehicle task assignment in atime-invariant drift field with obstacles

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DOI

  • Xiaoshan Bai
  • Weisheng Yan
  • Ming Cao
  • Dong Xue

This study investigates the task assignment problem where a fleet of dispersed vehicles needs to visit multiple target locations in a time-invariant drift field with obstacles while trying to minimise the vehicles' total travel time. The vehicles have different capabilities, and each kind of vehicles can visit a certain type of the target locations; each target location might require to be visited more than once by different kinds of vehicles. The task assignment problem has been proven to be NP-hard. A path planning algorithm is first designed to minimise the time for a vehicle to travel between two given locations through the drift field while avoiding any obstacle. The path planning algorithm provides the travel cost matrix for the target assignment, and generates routes once the target locations are assigned to the vehicles. Then, a distributed algorithm is proposed to assign the target locations to the vehicles using only local communication. The algorithm guarantees that all the visiting demands of every target will be satisfied within a total travel time that is at worst twice of the optimal when the travel cost matrix is symmetric. Numerical simulations show that the algorithm can lead to solutions close to the optimal.

Original languageEnglish
Pages (from-to)2886-2893
Number of pages8
JournalIET Control Theory and Applications
Volume13
Issue number17
Publication statusPublished - 26-Nov-2019

    Keywords

  • remotely operated vehicles, mobile robots, distributed algorithms, computational complexity, minimisation, total travel time, travel cost matrix, multivehicle task assignment, time-invariant drift field, task assignment problem, dispersed vehicles, multiple target locations, path planning algorithm, target assignment, distributed algorithm, numerical simulation, TARGET ASSIGNMENT, GENETIC ALGORITHM, ALLOCATION

ID: 111647584