首页|人工鱼群优化算法的移动机器人路径规划研究

人工鱼群优化算法的移动机器人路径规划研究

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针对传统人工鱼群算法在移动机器人全局路径规划中存在搜索效率比较低且路径冗余点比较多的问题,提出了基于双向搜索策略的人工鱼群算法.该算法通过正反两个方向交替检索路径的方式来进行全局路径规划,提高了算法在路径规划时的效率以及收敛速度.另外对于规划出的路径冗余节点以及不必要拐点较多的问题,通过对规划好的路径集引入路径平滑处理策略进行路径优化.仿真结果表明,改进后的人工鱼群算法与传统人工鱼群算法相比在收敛速度以及路径搜寻效率上均有较大的提高.最终将改进算法应用到实际的移动机器人中,实验结果证明,改进的算法可以有效解决移动机器人的路径规划问题.
Improved Artificial Fish Swarm Optimization Algorithm for Path Planning of Mobile Robot
Aiming at the problems of low search efficiency and many redundant points in the global path planning of mobile robots with traditional artificial fish swarm algorithm,an artificial fish swarm algorithm based on bidirectional search strategy was proposed.The algorithm performs global path planning by alternately retrieving paths in both positive and negative directions,which improves the efficiency and convergence speed of the algorithm in path planning.In addition,for the problem of redundant nodes and unnecessary inflection points in the planned path,the path smoothing strategy is introduced to optimize the planned path set.The simulation results show that the improved artificial fish swarm algorithm is better than the traditional artificial fish swarm algorithm in convergence speed and path search efficiency.Finally,the improved algorithm is applied to the actual mobile robot,and the experimental results show that the improved algorithm can effectively solve the global path planning problem of mobile robot.

mobile robotpath planningartificial fish swarm algorithmsmoothing strategy

马小陆、李成成、谭毅波、梅宏

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安徽工业大学 电气与信息工程学院,安徽马鞍山 243002

南京航空航天大学 航天学院,南京 210000

移动机器人 路径规划 人工鱼群算法 平滑处理策略

国家自然科学基金项目安徽省科技重大专项安徽高校自然科学研究重点项目安徽省重点研究开发计划特种重载机器人安徽省重点实验室开放课题项目安徽省高校协同创新项目

61472282202003a05020028KJ2019A0065202004a0502001TZJQR004-2020GXXT-2023-020

2024

机械科学与技术
西北工业大学

机械科学与技术

CSTPCD北大核心
影响因子:0.565
ISSN:1003-8728
年,卷(期):2024.43(10)