Event- and time-triggered dynamic task assignments for multiple vehicles: Special Issue on Multi-Robot and Multi-Agent Systems

Xiaoshan Bai*, Ming Cao, Weisheng Yan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

We study the dynamic task assignment problem in which multiple dispersed vehicles are employed to visit a set of targets. Some targets’ locations are initially known and the others are dynamically randomly generated during a finite time horizon. The objective is to visit all the target locations while trying to minimize the vehicles’ total travel time. Based on existing algorithms used to deal with static multi-vehicle task assignment, two types of dynamic task assignments, namely event-triggered and time-triggered, are studied to investigate what the appropriate time instants should be to change in real time the assignment of the target locations in response to the newly generated target locations. Furthermore, for both the event- and time-triggered assignments, we propose several algorithms to investigate how to distribute the newly generated target locations to the vehicles. Extensive numerical simulations are carried out which show better performance of the event-triggered task assignment algorithms over the time-triggered algorithms under different arrival rates of the newly generated target locations.
Original languageEnglish
Pages (from-to)877–888
Number of pages12
JournalAutonomous Robots
Volume44
Issue number5
Early online date2-Apr-2020
DOIs
Publication statusPublished - May-2020

Keywords

  • TARGET ASSIGNMENT
  • ALLOCATION
  • ALGORITHM
  • TAXONOMY

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