基于改进遗传算法的机器人主动嗅觉研究

Research on Robots Active Olfaction Based on Improved Genetic Algorithm

在基于遗传算法机器人主动嗅觉研究中,为了使机器人小车在特定的烟羽环境中,能够更快、更准确地寻找到气味源,通过对遗传算法交叉算子和变异算子的改进,形成一种新的改进遗传算法。在5个假设前提下,将改进遗传算法应用到机器人主动嗅觉研究中。仿真结果表明:与传统的遗传算法相比,采用改进遗传算法,机器人小车能够更快速、更准确地寻找到烟羽中的气味源。

In the research of robots active olfaetion based on genetic algorithm, in order to make the robot car in a specific plume environment, can be faster and more accurate to find the odor source, through improving the genetic algorithm crossover operator and mutation operator, a new improved genetic algorithm was formed. Based on five assumptions, the improved genetic algorithm was applied to the robot active olfaction study. Simulation results show that comparing with the traditional algorithm, the robot ear can be faster and more accurate in finding the odor plume source using the improved genetic algorithm.