基于Mirosot平台改进遗传算法避障策略  

Improved Genetic Algorithm for Obstacle Avoidance Based on Mirosot Platform

作　　者：孙绍华 王魁生[1] 张恬恬 SUN Shao hua;WANG Kui-sheng;ZHANG Tian tian(School of Computer Science,Xi'an Shiyou University,Xi'an 710065,China)

机构地区：[1]西安石油大学计算机学院,陕西西安710065

出　　处：《中北大学学报（自然科学版）》2019年第1期70-73,78,共5页Journal of North University of China(Natural Science Edition)

摘　　要：基于Mirosot机器人平台,考虑机器人自身构造对带球避障的影响,造成实际应用中机器人带球避障效果不佳的问题,首先对机器人构造进行剖析计算,提出机器人旋转限制角度δ;其次,改进遗传算法中的适应值函数,提出机器人带球避障路径规划情况下的适应值因子wk;最终,设计实验验证算法的可行性和有效性.实验分别设计静态和动态两种情况下的机器人避障,结果表明改进后的遗传算法有效降低了机器人带球避障时的丢球率,提高了机器人路径规划中带球避障的效率.Based on the Mirosot platform analysis of related obstacle avoidance path planning research,the research field of robot structure with the ball was found that has not been considered the influence of the obstacle avoidance,causing the ball robot obstacle avoidance in the practical application effect is not good.In order to solve the above problems,firstly,the robot structure was analyzed and the rotation limit Angle of the robotδwas proposed.Secondly,the adaptive value function of genetic algorithm was improved,and puts forward the adaptive value factor wkin the path planning of the robot.Finally,the feasibility and effectiveness of the experimental verification algorithm were presented.The static and dynamic robot obstacle avoidance experiments were designed respectively,experiments show that the improved genetic algorithm can effectively reduce the ball loss rate of the robot and improve the efficiency of avoiding the obstacle in the path planning of the robot.

关 键 词：MIROSOT 避障运动 路径规划 机器人足球 遗传算法 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]