基于模糊逻辑控制的自主导航采摘机器人避障设计

为了提高采摘机器人自主导航的环境适应能力,提出了一种基于改进的遗传算法的模糊学习逻辑控制方法,提高了机器人路径规划的能力和效率,缩短了路径规划所用时间。该方法以传感器测得的障碍物距离、轮转速和目标地点方向作为输入量,左右驱动轮的速比作为输出量,控制机器人的移动路径和方向。为了使机器人规划的路径尽量短,达到节能的目的,引入了改进的遗传算法,使用修正项对遗传算法进行改进,建立了适应度函数的基本模型。最后,对采摘机器人的性能进行了测试,通过测试发现:机器人可以成功地躲避障碍物,且能够完成最短路径规划,规划反应时间短、可靠性高。

Obstacle Avoidance Design for Picking Robot of Autonomous Navigation Based on Fuzzy Logic Control

In order to improve the adaptive ability of the robot's autonomous navigation, a fuzzy logic control method is proposed based on the improved genetic algorithm, which can improve the ability and efficiency of robot path planning, and shorten the time of path planning.The speed ratio of the driving wheel is used as the output quantity, and the path of the robot is controlled by the speed ratio of the driving wheel.The improved genetic algorithm is introduced.Finally, the performance of the picking robot is tested.Through the test, it is found that the robot can avoid the obstacle success-fully, finish the shortest path planning.And the planning response time is short, the reliability is high.