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The development of hybrid methods in simple swarm robots for gas leak localization

机译:气体泄漏定位简单群机器人混合方法的开发

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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.
机译:需要群体机器人的嗅觉系统来构建可靠的早期气体泄漏检测,以降低环境的不良影响。本文提出了与定位气体泄漏的混合方法,通过使用群机器人识别气体类型。该提出的混合方法与三种算法组合和三种功能,例如用于群体机器人导航的模糊逻辑系统,用于用于气体识别的群体机器人(SVM),以及用于路由优化的粒子群优化(PSO)。该研究的结果表明,该组方法可以实施,以便在真实实验中的室内环境下定位气体泄漏源。通过使用这种方法预期该研究,群体机器人能够识别天然气泄漏的来源并在短时间内定位目标,而不会与群体环境中的障碍碰撞。

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