无人机群:基于智能体建模的指挥控制策略设计与评估

Alexander G. Madey
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引用次数: 5

摘要

无人驾驶飞行器(uav)被广泛用于军事和民用目的。更小、更轻、更便宜的无人机的出现,为在一个有凝聚力的群体或“群”中部署大量小型、半自主的无人机提供了机会。与单个无人机相比,蜂群具有许多优势,例如更高的覆盖范围、数量冗余和更低的远程带宽需求。设计一个蜂群需要设计蜂群的行为,并找到有效的方法来控制行为,这样蜂群就可以被引导去完成它的任务。提出了一种发展无人机蜂群行为的方法和指挥控制C2策略。基于代理的建模工具包NetLogo用于创建两种任务类型:污染物羽流映射和船舶跟踪。当参数改变时,性能指标用于评估成功。该研究证明了基于智能体的建模在无人机群工程中的潜在用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unmanned Aerial Vehicle Swarms: The Design and Evaluation of Command and Control Strategies using Agent-Based Modeling
Unmanned aerial vehicles UAVs are being widely used for both military and civilian purposes. The advent of smaller, lighter, less expensive UAVs opens opportunities to deploy a large number of small, semi-autonomous UAVs in a cohesive group or "swarm". Swarms offer numerous advantages over single UAVs, such as higher coverage, redundancy in numbers and reduced long-range bandwidth requirements. Engineering a swarm requires designing the swarming behavior and finding effective ways to control the behavior so that the swarm can be directed to complete its mission. This paper presents an approach to developing UAV swarming behaviors and command and control C2 strategies to govern them. The agent-based modeling toolkit NetLogo is used to create two mission types: contaminant plume mapping and vessel tracking. Performance metrics are used to evaluate success as parameters are changed. This research demonstrates the potential usefulness of agent-based modeling in the engineering of UAV swarms.
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