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On the Throughput of the Common Target Area for Robotic Swarm Strategies

Author

Listed:
  • Yuri Tavares dos Passos

    (Centro de Ciências Exatas e Tecnológicas, Universidade Federal do Reconcâvo da Bahia, Rua Rui Barbosa, 710. Centro., Cruz das Almas 44380-000, Brazil
    School of Computing and Communications, Lancaster University, Bailrigg, Lancaster LA1 4WA, UK)

  • Xavier Duquesne

    (School of Computing and Communications, Lancaster University, Bailrigg, Lancaster LA1 4WA, UK)

  • Leandro Soriano Marcolino

    (School of Computing and Communications, Lancaster University, Bailrigg, Lancaster LA1 4WA, UK)

Abstract

A robotic swarm may encounter traffic congestion when many robots simultaneously attempt to reach the same area. This work proposes two measures for evaluating the access efficiency of a common target area as the number of robots in the swarm rises: the maximum target area throughput and its maximum asymptotic throughput. Both are always finite as the number of robots grows, in contrast to the arrival time at the target per number of robots that tends to infinity. Using them, one can analytically compare the effectiveness of different algorithms. In particular, three different theoretical strategies proposed and formally evaluated for reaching a circular target area: (i) forming parallel queues towards the target area, (ii) forming a hexagonal packing through a corridor going to the target, and (iii) making multiple curved trajectories towards the boundary of the target area. The maximum throughput and the maximum asymptotic throughput (or bounds for it) for these strategies are calculated, and these results are corroborated by simulations. The key contribution is not the proposal of new algorithms to alleviate congestion but a fundamental theoretical study of the congestion problem in swarm robotics when the target area is shared.

Suggested Citation

  • Yuri Tavares dos Passos & Xavier Duquesne & Leandro Soriano Marcolino, 2022. "On the Throughput of the Common Target Area for Robotic Swarm Strategies," Mathematics, MDPI, vol. 10(14), pages 1-38, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2482-:d:864353
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    References listed on IDEAS

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    1. Maria Mannone & Valeria Seidita & Antonio Chella, 2022. "Categories, Quantum Computing, and Swarm Robotics: A Case Study," Mathematics, MDPI, vol. 10(3), pages 1-11, January.
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