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.
作者
郭伟
秦国选
王磊
孙日杰
GUO Wei;QIN Guo-xuan;WANG Lei;SUN Ri-jie(College of Mechanical Engineering,Tianjin University,Tianjin 300354,China)
出处
《控制与决策》
EI
CSCD
北大核心
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)。
作者简介
通讯作者:郭伟(1965),男,教授,博士,从事现代设计理论方法与技术、人工智能、大数据等研究,E-mail:wguo@tju.edu.cn;秦国选(1994),男,硕士生,从事移动机器人的路径规划与导航的研究,E-mail:qin1021@tju.edu.cn;王磊(1976),男,副教授,从事现代设计理论方法与技术、人工智能等研究,E-mail:w2165@139.com;孙日杰(1992),男,硕士生,从事移动机器人视觉跟随的研究,E-mail:srjie@tju.edu.cn.
