Robots Active Olfaction Based on Improved Genetic Algorithm

Zhi-Biao Shi, Jiang-bo Sun
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Abstract

Robots active olfaction based on Genetic algorithm, in order to make the robot car plume in a specific environment, can be faster and more accurate to find the odor source, through the genetic algorithm crossover and mutation operator improved, the formation of a new improved genetic algorithm. In the five assumptions, will improve the genetic algorithm is applied to the robot active olfaction study, simulation results show that the genetic algorithm with the traditional comparison, the robot car can be faster and more accurate in finding the odor plume source.
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基于改进遗传算法的机器人主动嗅觉
基于遗传算法的机器人主动嗅探,为了使机器人在特定环境下,能够更快、更准确地找到气味源,通过对遗传算法的交叉和变异算子进行改进,形成了一种新的改进遗传算法。在这五个假设中,将改进的遗传算法应用于机器人主动嗅觉的研究,仿真结果表明,将遗传算法与传统的汽车机器人进行比较,可以更快、更准确地找到气味羽流源。
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