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Canadian Conference on Artificial Intelligence

Canadian AI 2019: Advances in Artificial Intelligence pp 486–491Cite as

A Generic Evolutionary Algorithm for Efficient Multi-Robot Task Allocations

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11489)

Abstract

Task allocation in multi-robot teams is conventionally carried out using customized algorithms against individual distributions due to their NP-hard nature. The expanding range of autonomous multi-robot operations demands for a generic allocation scheme capable of working across a variety of problem distributions. This paper presents an intelligently crafted, novel, evolutionary algorithm based task allocation scheme capable of working across a range of multi-robot problem distributions. Qualitative analysis against exact optimal solutions and a state of the art auction based scheme verify the capabilities of the proposed algorithm.

Keywords

  • Multi-Robot Task Allocation
  • Plan formulation
  • Evolutionary algorithm
  • Optimization

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  • DOI: 10.1007/978-3-030-18305-9_49
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Author information

Authors and Affiliations

  1. Institute of Business Administration, Karachi, Pakistan

    Muhammad Usman Arif

Authors
  1. Muhammad Usman Arif
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Correspondence to Muhammad Usman Arif .

Editor information

Editors and Affiliations

  1. University of Quebec in Montreal, Montreal, QC, Canada

    Marie-Jean Meurs

  2. University of Toronto, Toronto, ON, Canada

    Frank Rudzicz

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Arif, M.U. (2019). A Generic Evolutionary Algorithm for Efficient Multi-Robot Task Allocations. In: Meurs, MJ., Rudzicz, F. (eds) Advances in Artificial Intelligence. Canadian AI 2019. Lecture Notes in Computer Science(), vol 11489. Springer, Cham. https://doi.org/10.1007/978-3-030-18305-9_49

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  • DOI: https://doi.org/10.1007/978-3-030-18305-9_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18304-2

  • Online ISBN: 978-3-030-18305-9

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