Chemical Plume Tracing and Mapping via Swarm Robots

Wei Li, Yu Tian
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引用次数: 4

Abstract

This chapter addresses the key issues of chemical plume mapping and tracing via swarm robots. First, the authors present the models of turbulent odor plumes with both non-buoyant and buoyant features, which can efficiently evaluate strategies for tracing plumes, identifying their sources in two or three-dimensions. Second, the authors use the Monte Carlo technique to optimize moth-inspired plume tracing via swarm robots under formation control, which includes a leader to perform plume tracing maneuvers and non-leaders to follow the leader during plume tracing missions. Third, the authors introduce a variety of robot-based plume tracers, including ground-based robots, autonomous underwater vehicles, or unmanned aerial vehicles. Finally, the authors prospect the further research in this area, e.g., applying swarm robots to detect oil or gas leak, or to investigate subsea chemical pollution and greenhouse gases.
化学烟羽追踪和测绘通过蜂群机器人
本章讨论了通过群机器人进行化学羽流测绘和追踪的关键问题。首先,作者提出了具有非浮力和浮力特征的湍流气味羽流模型,该模型可以有效地评估追踪羽流的策略,并在二维或三维空间中识别其来源。其次,作者利用蒙特卡罗技术优化了在编队控制下由飞蛾启发的羽流追踪,其中包括一个领导者执行羽流追踪机动,非领导者在羽流追踪任务中跟随领导者。第三,作者介绍了各种基于机器人的羽流示踪剂,包括地面机器人、自主水下航行器或无人飞行器。最后,作者展望了该领域的进一步研究,例如应用群体机器人检测石油或天然气泄漏,或调查海底化学污染和温室气体。
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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