简单群机器人气体泄漏定位的混合方法研究

Husnawati, Gita Fadila Fitriana, S. Nurmaini
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引用次数: 6

摘要

为了减少气体泄漏对环境的不良影响,需要群体机器人的嗅觉系统来建立可靠的早期气体泄漏检测。本文提出了利用群机器人进行气体泄漏定位和气体类型识别的混合方法。提出了基于模糊逻辑系统的群体机器人导航、基于支持向量机(SVM)的气体识别和基于粒子群优化(PSO)的路径优化三种算法和三种功能的混合方法。研究结果表明,该方法可用于室内环境气体泄漏源的定位。本研究期望利用该方法,使群体机器人能够在短时间内识别气体泄漏源并定位目标,而不会与群体环境中的障碍物发生碰撞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The development of hybrid methods in simple swarm robots for gas leak localization
The olfactory system of swarm robot are needed to build reliable early gas leak detection, for decreasing the bad impact in the environment. This paper proposes hybrid methods related to locating the gas leak and identify the type of gas by using swarm robots. The propose hybrid methods combination with three algorithms and with three functions, such as the fuzzy logic system for swarm robot navigation, support vector machine (SVM) for gas identification, and particle swarm optimization (PSO) for route optimization. The result of this research shows the set of methods can be implemented to localize gas leak source at the indoor environment in a real experiment. This research is expected by using this method, the swarm robots have the ability to identify the source of the gas leak and localize the target in a short time without collision with the obstacle in the swarm environment.
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