基于改进RRT^(*)FN算法的机器人路径规划  

Robot path planning based on improved RRT^(*)FN algorithm

作　　者：谭建豪[1,2] 潘豹 王耀南[1,2] 崔昊韵 TAN Jian-hao;PAN Bao;WANG Yao-nan;CUI Hao-yun(College of Electrical and Information Engineering,Hunan University,Changsha 410082,China;National Engineering Laboratory for Robot Visual Perception and Control Technology,Hunan University,Changsha 410082,China)

机构地区：[1]湖南大学电气与信息工程学院,长沙410082 [2]湖南大学机器人视觉感知与控制技术国家工程实验室,长沙410082

出　　处：《控制与决策》2021年第8期1834-1840,共7页Control and Decision

基　　金：国家自然科学基金项目(61433016);湖南省科技创新计划项目(2017XK2102)。

摘　　要：针对固定节点数的渐近最优快速扩展随机数算法(RRT^(*)FN)精度低、收敛到最优值速度慢等问题,提出一种改进的RRT^(*)FN路径规划算法,并用于解决二维静态环境下的移动机器人全局路径规划问题.首先,改进算法使用与RRT^(*)FN算法相同的均匀采样方法进行路径搜索,当搜索到一条初始路径时,在之后的路径规划中使用启发式采样方法.在之后的每次迭代中,改进算法在椭圆子集采样方法与路径点邻近区域采样方法中随机选择一种作为当前采样方法.然后,当树中的总节点数达到预设值时,对树中的叶子结点采用加权方法进行删除.通过给予采样区域内的叶子结点更高的权重,从而将采样区域外的叶子结点以更高概率删除,得以保留树中的高性能节点,以便提高算法性能.最后,通过仿真实验验证改进算法的有效性.Aiming at the problems of low accuracy and slow convergence of rapidly-exploring random trees star fixed nodes(RRT^(*)FN)algorithms,this paper proposes an improved RRT^(*)FN path planning algorithm,which is used to solve the global path planning problem of mobile robots in the two-dimensional static environment.Firstly,the improved algorithm uses the same uniform sampling method as the RRT^(*)FN algorithm for path planning.When the improved algorithm gets an initial path,the heuristic sampling method will be used in subsequent path searching.In each next iteration,the improved algorithm randomly selects a method from the ellipse subset sampling method and the path point neighboring area sampling method as the current sampling method.Then,when the total number of nodes in the tree reaches the preset value,the leaf nodes in the tree are deleted using a weighted method.By giving higher weight to the leaf nodes in the sampling area,the leaf nodes outside the sampling area are deleted with a higher probability.Therefore,high-performance nodes in the tree can be retained,and algorithm performance is improved.Finally,the simulation experiments verify the effectiveness of the improved algorithm.

关 键 词：移动机器人 路径规划 改进RRT^(*)FN 启发式采样 初始路径 节点权重 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]