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Large-Scale Swarm Control in Cluttered Environments

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Social Robotics (ICSR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14453 ))

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Abstract

In the evolving era of social robots, managing a swarm of autonomous agents to perform particular tasks has become essential for numerous industries. The task becomes more challenging for large-scale swarms and complex environments, which have not been fully explored yet. Therefore, this research introduces a methodology incorporating multiple coordinated robotic shepherds to effectively guide large-scale agent swarms in obstacle-laden terrains. The proposed framework commences with deploying an unsupervised machine-learning algorithm to categorise the swarm into clusters. Then, a shepherding algorithm with coordinated robotic shepherds drives the sub-swarms towards the goal. Also, a path planner based on an evolutionary algorithm is proposed to help robotic shepherds move in a way that minimises the dispersion of each sub-swarm and avoids potential hazards and obstructions. The proposed approach is tested on different scenarios, with the results showing a success rate of 100% in guiding swarms with sizes up to 3000 agents.

This research is supported by UNSW Rector’s start-up grant (No. PS48058) and the U.S. Office of Naval Research-Global (ONR-G).

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Author information

Authors and Affiliations

  1. School of Systems and Computing, University of New South Wales, Canberra, Australia

    Saber Elsayed

  2. Mathematics Program, Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University, P.O. Box 2713, Doha, Qatar

    Mohamed Mabrok

Authors
  1. Saber Elsayed
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  2. Mohamed Mabrok
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Corresponding author

Correspondence to Saber Elsayed .

Editor information

Editors and Affiliations

  1. Qatar University, Doha, Qatar

    Abdulaziz Al Ali

  2. Qatar University, Doha, Qatar

    John-John Cabibihan

  3. Qatar University, Doha, Qatar

    Nader Meskin

  4. University of Naples Federico II, Napoli, Italy

    Silvia Rossi

  5. Qingdao University, Qingdao, China

    Wanyue Jiang

  6. The University of Alabama, Tuscaloosa, AL, USA

    Hongsheng He

  7. National University of Singapore, Queenstown, Singapore

    Shuzhi Sam Ge

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Elsayed, S., Mabrok, M. (2024). Large-Scale Swarm Control in Cluttered Environments. In: Ali, A.A., et al. Social Robotics. ICSR 2023. Lecture Notes in Computer Science(), vol 14453 . Springer, Singapore. https://doi.org/10.1007/978-981-99-8715-3_32

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  • DOI: https://doi.org/10.1007/978-981-99-8715-3_32

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8714-6

  • Online ISBN: 978-981-99-8715-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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