一种融合改进A^(*)算法与改进动态窗口法的文旅服务机器人路径规划  

A path planning for cultural tourism service robot combining improved A^(*) algorithm and improved dynamic window approach

作　　者：贾明超 冯斌 吴鹏[1] 张坤 桑胜举[2] JIA Mingchao;FENG Bin;WU Peng;ZHANG Kun;SANG Shengju(School of Information Science and Engineering,University of Jinan,Jinan Shandong 250022,China;School of Information Science and Technology,Taishan University,Tai’an Shandong 271000,China)

机构地区：[1]济南大学信息科学与工程学院,山东济南250022 [2]泰山学院信息科学技术学院,山东泰安271000

出　　处：《图学学报》2024年第3期505-515,共11页Journal of Graphics

基　　金：泰安市科技创新发展项目(2020ZC313)。

摘　　要：为满足复杂环境下文旅服务机器人路径规划算法搜索的导向性、静态环境下全局路径的最优性和动态环境下实时避障的安全性的需要,提出了一种基于改进A^(*)算法与动态窗口法相融合的算法。首先,在传统A^(*)算法的基础上,采用更精确的搜索邻域选取策略,并引入障碍物占用栅格率来量化地图信息,动态调节启发函数和权重系数;其次,引入安全距离概念,提出一种三次折线优化方法,剔除冗余节点和拐点,以提高路径的平滑性;针对狭窄通道环境,提出一种自适应圆弧优化方法,使路径更符合机器人的运动学约束。通过加入动态障碍物垂直距离代价函数,有效减少机器人与动态障碍物的冲突和碰撞风险;最后,将改进A^(*)算法与动态窗口法相融合,选取关键路径点作为动态窗口法的临时目标点,分段使用动态窗口法进行局部实时路径修正。实验结果表明,该融合算法同时具备搜索导向性、全局路径最优性和动态避障能力,能够安全快速到达目标点,具有一定的应用价值。To meet the needs for the guidance of algorithm search in a complex environment,the optimality of global path in a static environment,and the security of real-time obstacle avoidance in a dynamic environment for path planning of cultural and tourism service robots,an algorithm based on the fusion of the improved A^(*)algorithm and the dynamic window approach was proposed.Firstly,based on the traditional A^(*)algorithm,a more accurate search neighborhood selection strategy was adopted,the obstacle occupation grid rate was introduced to quantify map information,and the heuristic function and weight coefficients were dynamically adjusted.Secondly,the concept of safe distance was introduced,and a cubic polyline optimization method was proposed to eliminate redundant nodes and inflection points,enhancing the smoothness of the path.For the narrow channel environment,an adaptive arc optimization method was proposed to make the path more consistent with the kinematic constraints of the robot.The integration of the vertical distance cost function of dynamic obstacles effectively reduced the risk of conflicts and collisions between the robot and dynamic obstacles.Finally,the improved A^(*)algorithm was integrated with the dynamic window method,selecting the key path point as the temporary target point for the dynamic window method,and applying the dynamic window method segmentally for local real-time path correction.Experimental results demonstrated that this fusion algorithm has search guidance,global path optimality and dynamic obstacle avoidance capabilities,and can reach the target point safely and quickly,thus offering certain application value.

关 键 词：文旅服务机器人 环境建模 路径规划 实时避障 A^(*)算法 动态窗口法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]