用于移动机器人路径规划的增强型蛇优化算法  

Enhanced snake optimization algorithm for mobile robot path planning

作　　者：陆顺意 何庆 王艺蒙 李言博 LU Shunyi;HE Qing;WANG Yimeng;LI Yanbo(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China;Department of Computing,The Hong Kong Polytechnic University,Hongkong 999077,China)

机构地区：[1]贵州大学大数据与信息工程学院,贵州贵阳550025 [2]香港理工大学电子计算学系,中国香港999077

出　　处：《传感器与微系统》2023年第12期127-129,133,共4页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(62166006);贵州省科技计划资助项目(黔科合支撑[2023]一般093,黔科合ZK字[2021]335)。

摘　　要：针对蛇优化(SO)算法在路径规划过程中存在搜索效率比较低、收敛速度慢且寻优精度低等问题,提出了一种改进的蛇优化算法(GLSOA)。在全局勘探阶段采用莱维飞行扰动策略,以扩大算法搜索范围并丰富其种群多样性。同时,使用非线性收敛因子调节环境温度变化,以平衡算法的全局探索和局部开发能力。然后,在局部搜索阶段引入局部混沌搜索策略,以扩大混沌空间的搜索范围,提高算法的局部开发能力。最后,采用黄金正弦机制指引种群位置更新,缩小搜索范围,提高算法收敛精度和速度。仿真结果表明,改进的算法有效缩短了路径规划长度,算法的性能有了显著性的提高。Aiming at the problems of low search efficiency,slow convergence speed and low optimizing precision of snake optimization(SO)algorithm in path planning process,an improved snake optimization algorithm which fuses golden sine algorithm(Golden-SA)and Lévy flight(GLSOA)is proposed.Firstly,a Lévy flight perturbation strategy is used in global exploration stage to expand the search range of the algorithm and enrich its population diversity.At the same time,a nonlinear convergence factor is used to regulate the ambient temperature variation to balance the global exploration and local exploitation capabilities of the algorithm.Secondly,a local chaos search strategy is introduced in the local search stage to expand the search range of chaotic space and improve the local exploitation capability of the algorithm.Finally,the golden sine mechanism is used to guide the population position update to narrow the search range and improve the convergence precision and speed of the algorithm.Simulation results show that the improved algorithm effectively shortens the path planning length,and the performance of the algorithm is significantly improved.

关 键 词：蛇优化算法 非线性收敛因子 莱维飞行 Tent混沌搜索 黄金正弦策略 机器人路径规划 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]