基于改进Bi-RRT算法的机器鱼路径规划方法  

Robot fish path planning method based on improved Bi-RRT algorithm

作　　者：黄健堃 薛钢[1,2,3,4] 刘延俊[1,2,3,4] 王雨 李厚池 白发刚 HUANG Jiankun;XUE Gang;LIU Yanjun;WANG Yu;LI Houchi;BAI Fagang(School of Mechanical Engineering,Shandong University,Jinan 250061,Shandong,China;Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education,Shandong University,Jinan 250061,Shandong,China;National Demonstration Center for Experimental Mechanical Engineering Education,Shandong University,Jinan 250061,Shandong,China;Institude of Marine Science and Technology,Shandong University,Qingdao 266237,Shandong,China)

机构地区：[1]山东大学机械工程学院,山东济南250061 [2]山东大学高效洁净机械制造教育部重点实验室,山东济南250061 [3]山东大学机械工程国家级实验教学示范中心,山东济南250061 [4]山东大学海洋研究院,山东青岛266237

出　　处：《山东大学学报（工学版）》2024年第1期74-82,共9页Journal of Shandong University（Engineering Science）

基　　金：国家自然科学基金资助项目(52001186);山东省自然科学基金资助项目(ZR2020QE292);崂山实验室科技创新资助项目(LSKJ202203505-3)。

摘　　要：为提高机器鱼的水下路径规划效率,更好地完成水下工作,提出一种基于改进双向快速搜索随机树(bidirectional rapidly-exploring random trees,Bi-RRT)算法的机器鱼路径规划方法。以研制的混合驱动机器鱼为研究对象,介绍其结构模型和运动控制模式,为后续试验验证提供物理样机。针对Bi-RRT算法存在的采样随机、路径冗余、效率不高等问题,融合生长引导机制和连接强化机制改进Bi-RRT算法,加入生长引导机制,改善随机树生长随机、两树连接慢的问题;加入连接强化机制提高算法搜索速度。对搜索路径进行优化处理,通过剔除冗余节点、插入优化节点,改善路径质量,对路径进行平滑处理,使路径更适合机器鱼航行,实现机器鱼路径规划任务。仿真结果表明,与传统Bi-RRT算法及其他衍生快速搜索随机树(rapidly-exploring random tree,RRT)算法相比,改进的Bi-RRT算法相较于改进前节点数减少约50.8%,路径长度缩短约19%,搜索时间减少约65.3%。In order to improve the efficiency of underwater path planning for robotic fish and better complete underwater work,a path planning method for robotic fish based on improved bidirectional rapidly-exploring random trees(Bi-RRT) algorithm was proposed.A hybrid drive robotic fish was developed as the research object,and its structural model and motion control mode were introduced,which provided a physical prototype for subsequent experimental verification.In response to the problems of sampling randomness,path redundancy,and low efficiency in the Bi-RRT algorithm,a growth guidance mechanism and connection strengthening mechanism were integrated to improve the Bi-RRT algorithm,and a growth guidance mechanism was added to improve the problem of random tree growth and slow connection between two trees;added connection reinforcement mechanism to improve algorithm search speed.The search path was optimized by removing redundant nodes and inserting optimization nodes to improve path quality.The path was smoothed to make it more suitable for robot fish navigation and to achieve robot fish path planning tasks.The simulation results showed that compared with the traditional Bi-RRT algorithm and other derived rapidly-exploring random tree(RRT) algorithms,the improved Bi-RRT algorithm reduced the number of nodes by about 50.8%,the path length by about 19%,and the search time by about 65.3% compared to the previous one.

关 键 词：机器鱼 Bi-RRT算法 路径规划 节点简化 路径平滑 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]