基于自适应步长果蝇算法的爬行机器人足端轨迹规划  

Foot Trajectory Planning of Creeping Robot Based on Adaptive Step Fruit Fly Optimization Algorithm

作　　者：周理 朱红求[2] ZHOU Li;ZHU Hongqiu(School of Mechaniccal and Electrical Engineering,Hunan City University,Yiyang Hunan 413000,China;School of Automation,Central South University,Changsha 410083,China)

机构地区：[1]湖南城市学院机械与电气工程学院,湖南益阳413000 [2]中南大学自动化学院,长沙410083

出　　处：《机械设计与研究》2021年第3期60-63,73,共5页Machine Design And Research

基　　金：国家自然科学基金资助项目(61773403)。

摘　　要：爬行机器人的足端轨迹规划是一个复杂多维难求解的问题,为此,提出一种自适应步长果蝇算法(ASFOA)并用于该问题的求解。ASFOA变果蝇算法(FOA)中的固定步长为自适应步长,增强了算法跳出局部最优和全局寻优的能力。典型测试函数的仿真结果表明了ASFOA相比于FOA的优势;在爬行机器人足端轨迹规划的实际应用中,同样是ASFOA获得了比FOA更好的结果。仿真测试和实际应用均验证了该方法具有一定的优势。Foot trajectory planning problem of creeping robot is a multi-dimensional and complex problem which is hardly to solve.Therefore,adaptive step fruit fly optimization algorithm(ASFOA)is proposed and used to solve this problem.The changeless step in fruit fly optimization algorithm(FOA)is instead by adaptive step which used in ASFOA,and the ability of the algorithm to break away from the local optimum and to find the global optimum is greatly enhanced.Experimental results of several typical functions show that ASFOA has the advantages when compared with FOA.In the practical application of foot trajectory planning of creeping robot,the ASFOA also obtained better results than FOA.Simulation test and practical application all showed that the method is also has a certain advantage.

关 键 词：自适应步长 果蝇算法 爬行机器人 轨迹规划 

分 类 号：TP206.3[自动化与计算机技术—检测技术与自动化装置]