article

Autonomous task allocation by artificial evolution for robotic swarms in complex tasks

Authors:

Motoaki Hiraga,

Kazuhiro Ohkura,

Zlatan CarAuthors Info & Claims

Artificial Life and Robotics, Volume 24, Issue 1

Pages 127 - 134

https://doi.org/10.1007/s10015-018-0466-6

Published: 01 March 2019 Publication History

Abstract

Swarm robotics is a field in which multiple robots coordinate their collective behavior autonomously to accomplish a given task without any form of centralized control. In swarm robotics, task allocation refers to the behavior resulting in robots being dynamically distributed over different sub-tasks, which is often required for solving complex tasks. It has been well recognized that evolutionary robotics is a promising approach to the development of collective behaviors for robotic swarms. However, the artificial evolution often suffers from two issues--the bootstrapping problem and deception--especially when the underlying task is profoundly complex. In this study, we propose a two-step scheme consisting of task partitioning and autonomous task allocation to overcome these difficulties. We conduct computer simulation experiments where robotic swarms have to accomplish a complex collective foraging problem, and the results show that the proposed approach leads to perform more effectively than a conventional evolutionary robotics approach.

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Cited By

Debie EKasmarik KGarratt M(2023)Swarm Robotics: A Survey from a Multi-Tasking PerspectiveACM Computing Surveys10.1145/361165256:2(1-38)Online publication date: 15-Sep-2023
https://dl.acm.org/doi/10.1145/3611652
Narvekar PVardy A(2023)A data grid strategy for non-prehensile object transport by a multi-robot systemArtificial Life and Robotics10.1007/s10015-023-00908-528:4(680-689)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1007/s10015-023-00908-5
Hiraga MKatada YOhkura K(2023)Echo state networks for embodied evolution in robotic swarmsArtificial Life and Robotics10.1007/s10015-022-00828-w28:1(139-147)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1007/s10015-022-00828-w
Show More Cited By

Autonomous task allocation by artificial evolution for robotic swarms in complex tasks
1. Computer systems organization
  1. Embedded and cyber-physical systems
2. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Planning and scheduling

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Information & Contributors

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Published In

cover image Artificial Life and Robotics

Artificial Life and Robotics Volume 24, Issue 1

March 2019

134 pages

ISSN:1433-5298

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Copyright © Copyright © 2019 International Society of Artificial Life and Robotics (ISAROB).

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 March 2019

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Cited By

Debie EKasmarik KGarratt M(2023)Swarm Robotics: A Survey from a Multi-Tasking PerspectiveACM Computing Surveys10.1145/361165256:2(1-38)Online publication date: 15-Sep-2023
https://dl.acm.org/doi/10.1145/3611652
Narvekar PVardy A(2023)A data grid strategy for non-prehensile object transport by a multi-robot systemArtificial Life and Robotics10.1007/s10015-023-00908-528:4(680-689)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1007/s10015-023-00908-5
Hiraga MKatada YOhkura K(2023)Echo state networks for embodied evolution in robotic swarmsArtificial Life and Robotics10.1007/s10015-022-00828-w28:1(139-147)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1007/s10015-022-00828-w
Hiraga MOhkura K(2022)Topology and weight evolving artificial neural networks in cooperative transport by a robotic swarmArtificial Life and Robotics10.1007/s10015-021-00716-927:2(324-332)Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1007/s10015-021-00716-9

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