基于改进人工鱼群算法和MAKLINK图的机器人路径规划  

Robot path planning based on improved artificial fish swarm algorithm and MAKLINK graph

作　　者：郭伟[1] 秦国选 王磊[1] 孙日杰 GUO Wei;QIN Guo-xuan;WANG Lei;SUN Ri-jie(College of Mechanical Engineering,Tianjin University,Tianjin 300354,China)

机构地区：[1]天津大学机械工程学院,天津300354

出　　处：《控制与决策》2020年第9期2145-2152,共8页Control and Decision

基　　金：国家社科重点基金项目(16AZD004)。

摘　　要：针对静态二维环境下移动机器人全局路径规划问题,提出一种基于改进人工鱼群算法(IAFSA)和MAKLINK图的路径规划方法.该方法以Lorentzian函数和正态分布函数为视野和步长的自适应算子,引入指数递减惯性权重因子,能够提高AFSA算法的收敛速度和计算精度. MS (JoséLuis Esteves Dos Santos)算法结合IAFSA算法分步寻优,取IAFSA算法优化后的最优路径为全局最优路径,可以解决以往算法在MAKLINK图中只能求近似全局最优路径的问题.仿真实验结果表明了所提出改进算法方案的可行性和有效性.A global path planning method, based on the improved artificial fish swarm algorithm(IAFSA) and MAKLINK graph,is proposed to solve the global path planning problem in the two-dimensional static environment.Lorentzian function and normal distribution function are chosen as adaptive operators of step and visual, the exponential decreasing inertia weighting factor is also introduced, which can improve the convergence speed and accuracy of the AFSA algorithm.The MS algorithm is combined with the IAFSA algorithm to calculate for two steps. The optimal path optimized by the IAFSA algorithm is selected as the global optimal path, which solves the problem of that the previous algorithm can only get the approximate global optimal path in the MAKLINK graph. The simulation results show the feasibility and effectiveness of the proposed improved algorithm.

关 键 词：移动机器人 路径规划 人工鱼群算法 MAKLINK图 MS算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]