Genetic Algorithm Based Optimization Technique for Route Planning Of Wheeled Mobile Robot

K. Sundaran
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引用次数: 2

Abstract

In recent years, the significant uplift in artificial intelligence and other related electrical and mechanical integration technology made the robots to play an important role in modern life. In the study of mobile robot, trajectory planning has always been an important issue. With the presence of obstacles in the work environment, the best principles of finding the right path with obstacle avoidance method as a basis for moving the mobile robot from the starting point to the end point. In most studies, these principles are often optimized for the shortest or safest path chosen with least time-consuming, thus resulting in planning the route. Smooth path is extremely important for the navigation of the mobile robot. It avoids the process of moving tire slippage caused serious error location of conjecture. Further, the structure of the robot operation is indispensable due to limitations caused by the smoothness of the path of the carrier class of models. Therefore, this proposed algorithm studied and combined the genetic optimization technique with B Spline to provide the mobile robot to plan the route globally in a static environment.
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基于遗传算法的轮式移动机器人路径规划优化技术
近年来,人工智能和其他相关机电一体化技术的显著提升,使机器人在现代生活中发挥了重要作用。在移动机器人的研究中,轨迹规划一直是一个重要的问题。在工作环境中存在障碍物的情况下,以避障方法寻找正确路径的最佳原则作为移动机器人从起点移动到终点的依据。在大多数研究中,这些原则往往是优化为选择最短或最安全的路径,并花费最少的时间,从而规划路线。平滑路径对于移动机器人的导航是非常重要的。它避免了移动过程中轮胎打滑造成的严重定位误差的臆测。此外,由于运载类模型的路径的平滑性所造成的限制,机器人的操作结构是必不可少的。因此,该算法研究并结合遗传优化技术和B样条,为移动机器人提供静态环境下的全局路径规划。
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