Cited by 38Modular Robots and Swarm IntelligenceDistributed Control Multi-Agent SystemsMetaheuristic Optimization Algorithms Research

Division of labor in a swarm of autonomous underwater robots by improved partitioning social inhibition

Zahadat, Payam, Schmickl, Thomas·2016·Adaptive Behavior

Abstract

In this paper, a distributed algorithm for adaptive task allocation and adaptable partitioning of a swarm into different work-groups is proposed and used in a swarm of underwater robots. The algorithm is based on local interactions of agents and is inspired by honeybee age-polyethism. It is adaptive to changes in the swarm size (workforce) and relative demands (workload) for different tasks and it limits the number of switchings of agents between different tasks enabling specialization of agents. The preliminary version of the algorithm was introduced previously. Here a fully decentralized version of the algorithm is proposed that improves the previous version by removing the need for global information. The algorithm is successfully implemented in swarms of physically-embodied underwater robots while the swarm size and the demands for the tasks change over the course of the experiments.

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Crossref · 10.1177/1059712316633028

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  • Natural self-organizing systems (e.g., social insects, fish schools, bird flocks) are characterized by emergent collective behavior based on simple local interaction rules.

    “It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent collective behavior based on simple local interaction rules [1], [2].”

    From Swarm Robotics: Past, Present, and Future [Point of View] (2021) · cites this paper as [1]

  • Self-organization in homogeneous systems has been often sufficient to explain experimental observations to a great degree.

    “As a matter of fact, self-organization in homogeneous systems has been often sufficient to explain experimental observations to a great degree [1].”

    From Swarm Robotics: Past, Present, and Future [Point of View] (2021) · cites this paper as [1]

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Authors
Zahadat, P., & Schmickl, T.
Affiliations
University of Graz (AT)
Corresponding author
Zahadat, Payam
Venue
Adaptive Behavior
Published
2016-03-08
Volume
24
Issue
2
Pages
87-101
ISSN
  • 1059-7123 (ISSN-L)
  • 1741-2633
OpenAlex
W2304063466
Cited by
38
References
39
Citations by year
2026: 3 · 2025: 3 · 2024: 2 · 2023: 9 · 2022: 5 · 2021: 4 · 2020: 4 · 2019: 3 · 2018: 3 · 2017: 2
FWCI
2.37
Type
journal article
Language
en
Open access
closed
Locations
Adaptive Behavior (publishedVersion)
Topics
  • Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Control Multi-Agent Systems
  • Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
Keywords
division of labor, autonomous underwater vehicles, task allocation, social inhibition, decentralized algorithms, task specialization

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