Auction-based task allocation scheme for dynamic coalition formations in limited robotic swarms with heterogeneous capabilities

Muhammad Irfan, A. Farooq
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引用次数: 27

Abstract

Task allocation is one of the main issues to be addressed in the domain of multi-robot systems, in which it is determined which robot(s) should execute which task(s) so that overall system goal is achieved. Such collective decision making process is of great significance during complex task execution by swarm of simple robots with heterogeneous capabilities. This work targets the issue of coalition formations in a limited swarm of robots to perform a task requiring multiple single-task robots (ST-MR-IA) depending upon their heterogeneous capability conditions. Capabilities of individual robots may vary to different certain levels in a dynamic environment during task execution which can further affect the coalition formed to execute a specific complex task requiring certain level of collective/group capability. This study aims to suggest an algorithm for task allocations through auction mechanism to form a new or modify a coalition underway, where individual robots may gain or lose their task capabilities at certain time instants. Effectiveness of proposed algorithm in terms of task-execution time and utility of coalitions is analyzed through simulations.
具有异构能力的有限机器人群动态联盟编队的竞价任务分配方案
任务分配是多机器人系统中需要解决的主要问题之一,任务分配是确定哪些机器人应该执行哪些任务,从而实现系统的总体目标。这种集体决策过程对具有异构能力的简单机器人群执行复杂任务具有重要意义。这项工作的目标是在有限的机器人群中形成联盟,根据它们的异构能力条件执行需要多个单任务机器人(ST-MR-IA)的任务。在任务执行的动态环境中,单个机器人的能力可能会发生一定程度的变化,进而影响为执行特定复杂任务而形成的联盟,这需要一定程度的集体/群体能力。本研究旨在提出一种通过拍卖机制进行任务分配的算法,以形成一个新的或修改正在进行的联盟,其中单个机器人可能在特定时刻获得或失去其任务能力。通过仿真分析了该算法在任务执行时间和联盟效用方面的有效性。
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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