基于IF&IABC算法的多机器人路径规划研究  

Research on Multi-robot Path Planning Based on IF&IABC Algorithm

作　　者：王希宇 魏赟[1] WANG Xiyu;WEI Yun(School of Optical-Electronic Information and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《计算机与数字工程》2022年第6期1233-1238,1353,共7页Computer & Digital Engineering

基　　金：国家重点研究计划项目(编号:2018YFB1700902)资助。

摘　　要：论文结合改进的蜂群算法和改进的模糊算法,为解决机器人路径规划问题提出了一种新的方法,即IF&IABC(Improved Fuzzy&Improved Artificial Bee Colony)算法。对人工蜂群算法进行改进,首先利用混沌思想和反向学习策略初始化种群,通过免疫信息调节机制在当前解和反向解之间进行选择,扩大种群多样性,增强跳出局部最优的能力;通过引入量子策略改进邻域搜索,引入独立的惯性权重来调节全局和局部寻优能力;采用边界变异法避免算法在搜索的过程中陷入局部最优。同时,结合具有速度反馈的模糊算法规划机器人的避障行为,从而控制机器人在特定状态下准确方便地改变路径,保证其在最佳状态下运行到目标点。实验结果证明论文算法步骤简捷,能很好解决不同机器人数量与不同任务目标点数量情况下的路径规划,且具有较大的实用性。In this paper,an improved fuzzy&improved artificial bee colony(IF&IABC)algorithm is proposed to solve the robot path planning problem by combining the improved bee colony algorithm and the improved fuzzy algorithm.The artificial bee colony algorithm is improved.Firstly,chaos and reverse learning strategy are used to initialize the population,and immune information regulation mechanism is used to select between the current solution and the reverse solution,so as to expand the diversity of the population and enhance the ability to jump out of the local optimum.Secondly,the quantum strategy is introduced to improve the neighborhood search,and the independent inertia weight is introduced to adjust the global and local optimization ability.The boundary mutation method is used to avoid the algorithm falling into local optimum in the process of searching.At the same time,the fuzzy algorithm with speed feedback is combined to plan the obstacle avoidance behavior of the robot,so as to control the robot to change the path accurately and conveniently in a specific state,so as to ensure that it can run to the target point in the optimal state.The experimental results show that the algorithm is simple,it can solve the path planning of different number of robots and different number of task target points,and has great practicability.

关 键 词：多机器人 路径规划 蜂群算法 模糊算法 IF&IABC 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]