基于飞蛾羽流追踪策略的源识别算法优化

Wei Li, Joseph E. Sutton
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引用次数: 4

摘要

本文提出了一种基于单个化学传感器的源识别算法的设计和优化方法,该算法来源于飞蛾启发的化学羽流追踪(CPT)策略。在此过程中,我们使用最后化学检测点(LCDPs)定义源识别区(SIZ)。然后,考虑REMUS车辆的动力学特性,利用具有明显曲流和灯丝间歇性的模拟羽流对算法进行了优化。仿真研究表明,经过1000次试运行,优化算法识别源位置的成功率达到90%以上,平均识别时间为3 ~ 4分钟,在100米长度尺度的作业区域内,识别源位置的平均误差为1~2米。此外,我们讨论了飞蛾启发策略的扩展,以追踪羽流并识别在三维空间中具有静态位置的气味源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Source Identification Algorithm Derived from Moth-Inspired Plume Tracing Strategies
This paper presents a method of designing and optimizing a single chemical sensor-based source identification algorithm, derived from moth-inspired chemical plume tracing (CPT) strategies. In doing it, we define a source identification zone (SIZ) using last chemical detection points (LCDPs). Then, we optimize the proposed algorithm using a simulated plume with significant meander and filament intermittency by considering dynamics of a REMUS vehicle. The simulation studies show that for 1000 test runs the optimized algorithm achieves a success rate of over 90% in identifying source locations, an average identification time of 3-4 minutes, and an average error of identified source locations 1~2 meters in an operation area with length scales of 100 meters. In addition, we discuss an extension of the moth-inspired strategies to trace a plume and identify the odor source with static location in a three-dimensional space.
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