OS17-7 Iterative Method of Labor Division for Multi-Robotic Systems

Title:	OS17-7 Iterative Method of Labor Division for Multi-Robotic Systems
Publication:	ICAROB2022
Volume:	27
Pages:	699-702
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2022.OS17-7
Author(s):	Sergey Ryabtsev, Artur Sakolchik, Vladimir Antonov, Vyacheslav Petrenko, Fariza Tebueva, Sergey Makarenko
Publication Date:	January 20, 2022
Keywords:	Multi-robotic systems, swarm robotics, task allocation, division of labor, collective decision making
Abstract:	Labor division in multi-robotic systems allows distributing tasks between agents in order to increase the efficiency of performing the global task. Collective decision-making methods allow agents to form the "agent-task" pairs. In this paper, we consider the case when the number of tasks significantly exceeds the number of agents. We propose an iterative method of labor division in multi-robotic systems. It uses collective decision-making to assign a cluster of subtasks to an agent. The paper examines different ratios between cluster size, number of clusters, and number of agents in order to find ratios that provide minimal average global task execution time and minimal average energy consumption.
PDF File:	https://alife-robotics.co.jp/members2022/icarob/data/html/data/OS/OS17/OS17-7.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/

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