Distributed and decentralized task allocation for heterogeneous swarms

IF 0.8 Q4 ROBOTICS
Yigal Koifman, Ariel Barel, Alfred M. Bruckstein
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引用次数: 0

Abstract

This paper presents a multi-layered framework for fully distributed and decentralized task allocation in heterogeneous swarms, derived from interaction-based dynamics. This approach is built upon a baseline of homogeneous swarms composed of simple, autonomous, identical, locally sensing agents. Agents operate under the “flexible swarm” paradigm, which promotes global cohesion through local interactions that prevent swarm fragmentation. We demonstrate how a desired swarm behavior of exploration, task detection, and requirement fulfillment can emerge from local motion rules based solely on self-sensing without explicit inter-agent communication. Starting from a homogeneous baseline of identical agents, we extend the framework to heterogeneous swarms composed of agents with varying sensing capabilities and payloads. We introduce a novel interaction scheme in which two homogeneous groups, scouts and fire-extinguishers, are functionally coupled through local sensing, forming an emergent heterogeneous system. This coupled coordination enables distributed fire detection and suppression, enhancing robustness and scalability. The framework is validated through firefighting simulations, utilizing a heterogeneous swarm composed of scout agents with long-range sensing and fire-extinguishing agents with limited perception and actuation abilities. Through simple local motion rules, agents self-organize to detect and extinguish fires in a cooperative manner, driven solely by local sensing and interaction forces. Various fire suppression simulations demonstrate clear trade-offs between scouting and fire-extinguishing capacities. Our simulation results show that scouting dominates overall performance, whereas adding more fire-extinguishers provides only marginal improvement beyond a critical ratio. The results demonstrate that decentralized control of heterogeneous swarms enhances scalability, robustness, and efficiency even under direct communication denial. A simulation video demonstrating the proposed framework, illustrating the emergent coordination, task allocation dynamics, and analysis of a specific scenario, is available at https://youtu.be/dZqVxlhhzYc.

异构集群的分布式和分散式任务分配
本文从基于交互的动力学理论出发,提出了异构集群中完全分布式和分散任务分配的多层框架。这种方法是建立在由简单的、自主的、相同的、局部感知代理组成的同质群体的基线上的。智能体在“灵活的群体”模式下运行,通过局部互动促进全局内聚,防止群体分裂。我们展示了一个理想的群体行为的探索,任务检测,和需求的实现可以从局部运动规则出现,仅基于自我感知,没有明确的代理间通信。从相同代理的同质基线开始,我们将框架扩展到由具有不同感知能力和有效负载的代理组成的异构群。我们提出了一种新的相互作用方案,其中两个同质群体,侦察兵和灭火器,通过局部感知功能耦合,形成一个紧急异质系统。这种耦合协调使分布式火灾探测和抑制成为可能,增强了鲁棒性和可扩展性。通过消防模拟验证了该框架,利用具有远程传感的侦察代理和具有有限感知和驱动能力的灭火剂组成的异构群。通过简单的局部运动规则,智能体自组织以合作的方式探测和扑灭火灾,仅由局部感知和相互作用的力量驱动。各种灭火模拟清楚地展示了侦察和灭火能力之间的权衡。我们的模拟结果表明,侦察在整体性能上占主导地位,而增加更多的灭火器只提供了超过临界比例的边际改进。结果表明,即使在直接拒绝通信的情况下,异构群的分散控制也能提高可扩展性、鲁棒性和效率。仿真视频演示了所提出的框架,说明了紧急协调,任务分配动态和特定场景的分析,可在https://youtu.be/dZqVxlhhzYc上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.00
自引率
22.20%
发文量
101
期刊介绍: Artificial Life and Robotics is an international journal publishing original technical papers and authoritative state-of-the-art reviews on the development of new technologies concerning artificial life and robotics, especially computer-based simulation and hardware for the twenty-first century. This journal covers a broad multidisciplinary field, including areas such as artificial brain research, artificial intelligence, artificial life, artificial living, artificial mind research, brain science, chaos, cognitive science, complexity, computer graphics, evolutionary computations, fuzzy control, genetic algorithms, innovative computations, intelligent control and modelling, micromachines, micro-robot world cup soccer tournament, mobile vehicles, neural networks, neurocomputers, neurocomputing technologies and applications, robotics, robus virtual engineering, and virtual reality. Hardware-oriented submissions are particularly welcome. Publishing body: International Symposium on Artificial Life and RoboticsEditor-in-Chiei: Hiroshi Tanaka Hatanaka R Apartment 101, Hatanaka 8-7A, Ooaza-Hatanaka, Oita city, Oita, Japan 870-0856 ©International Symposium on Artificial Life and Robotics
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