Multi-robot task allocation using clustering method

Farzam Janati, Farzaneh Abdollahi, Saeed Shiry Ghidary, Masoumeh Jannatifar, Jacky Baltes, Soroush Sadeghnejad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper introduces an approach to solve the task assignment problem for a large number of tasks and robots in an efficient time. This method reduces the size of the state space explored by partitioning the tasks to the number of robotic agents. The proposed method is divided into three stages: first the tasks are partitioned to the number of robots, then robots are being assigned to the clusters optimally, and finally a task assignment algorithm is executed individually at each cluster. Two methods are adopted to solve the task assignment at each cluster, a genetic algorithm and an imitation learning algorithm. To verify the performance of the proposed approach, several numerical simulations are performed. Our empirical evaluation shows that clustering leads to great savings in runtime (up to a factor of 50), while maintaining the quality of the solution.

Original languageEnglish
Title of host publicationRobot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications
EditorsFakhri Karray, Jong-Hwan Kim, Hyun Myung, Jun Jo, Peter Sincak
PublisherSpringer Verlag
Pages233-247
Number of pages15
ISBN (Print)9783319312910
DOIs
Publication statusPublished - 2017
Event4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015 - Bucheon, Korea, Republic of
Duration: 2015 Dec 142015 Dec 16

Publication series

NameAdvances in Intelligent Systems and Computing
Volume447
ISSN (Print)2194-5357

Other

Other4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015
CountryKorea, Republic of
CityBucheon
Period15/12/1415/12/16

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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