Guidelines for improving the robustness of swarm robotic systems through adjustment of network topology

Xinran Wang, David Green, Jan Carlo Barca

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    3 Citations (Scopus)

    Abstract

    Swarm Robotics (SR) is expected to have a significant impact on society over the next decade. One of the contributing factors is that swarms are robust. However, robustness has not gained sufficient attention in the context of robotic swarms. This study focuses on the swarm network to generate insights as to how network topologies can be controlled to improve the robustness of SR systems. More specifically, how removing key robots alters the network topology, thereby changing the performance of the swarm. Analyzing these changes provides possible guidelines to improve swarm robustness towards targeted interventions. The most important findings suggest that robustness can be increased by making the network topology: (1) provincial and decentralized in the middle phase of the swarming procedure in unimodal domains, (2) provincial and centralized during the same phase in multi-objective domains.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)
    EditorsOliver Sawodny
    Place of PublicationPiscataway NJ USA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1399-1405
    Number of pages7
    ISBN (Electronic)9781509060009, 9781509059997
    ISBN (Print)9781509060016, 9781509059980
    DOIs
    Publication statusPublished - 21 Aug 2017
    EventIEEE/ASME International Conference on Advanced Intelligent Mechatronics 2017 - Munich, Germany
    Duration: 3 Jul 20177 Jul 2017
    Conference number: 16th
    http://www.aim2017.org/ (Conference website)
    http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7999201 (Proceedings)

    Conference

    ConferenceIEEE/ASME International Conference on Advanced Intelligent Mechatronics 2017
    Abbreviated titleAIM 2017
    Country/TerritoryGermany
    CityMunich
    Period3/07/177/07/17
    Internet address

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