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针对室内环境下的服务型移动机器人路径规划问题,分析并比较了两种经典算法——Dijkstra算法及基于Manhattan估计函数的A*算法,通过改变A*算法估价函数中参数的权值来优化路径轨迹,从而既满足A*算法的可接纳性,同时又实现两种算法的融合.在VC环境下编译出路径规划的仿真程序,通过变换起始点与目标点的坐标,比较运算时间和生成的路径轨迹.结果显示:加权A*算法优化了A*算法的路径轨迹,且在计算时间上优于Dijkstra算法,解决了服务型移动机器人的路径规划问题,满足实时性要求.
In order to solve the routing problem of service-oriented mobile robot in indoor environment, two classical algorithms, Dijkstra algorithm and A * algorithm based on Manhattan estimation function, are analyzed and compared. The path of A * algorithm is optimized by changing the weight of parameters in the function Trajectory, so as to satisfy the admissibility of A * algorithm and realize the fusion of the two algorithms at the same time.A simulation program of path planning is compiled under the VC environment, and the coordinates of the starting point and the target point are transformed to compare the computing time and the generated The results show that the weighted A * algorithm optimizes the path of A * algorithm and is superior to Dijkstra algorithm in computing time, which solves the path planning problem of service-oriented mobile robot and meets the real-time requirements.