多机器人多交会充电模式:机会控制策略

Soheil Keshmiri
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引用次数: 6

摘要

针对多机器人多交会充电问题,提出了一种机会控制方法。该控制策略在解决问题时尝试利用集中式和分布式方法的优势。群体中的每个机器人代理都配备了一个决策引擎,该决策引擎通过与负责为机器人代理充电寻找能量的母机器人通信获得可用的交会位置。虽然该决策引擎为个体提供了自主选择集合地点的权利,但由母机器人执行的中心集合估计机制可以防止由于智能体无充电和/或智能体在可充电集合地点分布不均而导致的系统故障。演示了可能归因于代理决策引擎的属性。给出了该方法的仿真结果和性能分析,并与其他充电方法和技术进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-robot, multi-rendezvous recharging paradigm: An opportunistic control strategy
This paper presents an opportunistic control approach to address the multi-robot, multi-rendezvous recharging problem. The control strategy adapted attempts to take advantages of both centralized as well as distributed methodologies while addressing the problem. Every robotic agent of the group is equipped with a decision engine that scores available rendezvous locations that are obtained via communicating with mother robot that is in-charge of recharging the robotic agents in search of energy. While such decision engine provides autonomy to individuals to finalize their corresponding choice of rendezvous locations, the central rendezvous estimation mechanism that is performed by mother robots prevents system failure that may incur due to out-of-charge agents and/or uneven distribution of agents over available recharging rendezvous locations. Properties that might be attributed to agents' decision engine are demonstrated. Simulation results and performance analysis of the proposed approach along with comparisons to alternative recharging methodologies and techniques have been presented.
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