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基于改进AG算法的机器人动态路径规划方法
引用本文:王 楠,张 军,解 鹏.基于改进AG算法的机器人动态路径规划方法[J].河北工业科技,2018,35(3):178-184.
作者姓名:王 楠  张 军  解 鹏
作者单位:河北工业大学计算机科学与软件学院
基金项目:天津市自然科学基金(14JCYBJC18500)
摘    要:为了充分发挥Agoraphilic(AG)算法的优越性,使其可以在动态环境中有效地进行路径规划,对传统AG算法进行了研究和改进,在计算自由空间力时增加了机器人和动态障碍物之间的相对速度分量,该分量可分解为2个方向的分力,一个分力使机器人向背离障碍物的方向运动,另一个分力使机器人向垂直于障碍物的方向运动,充当机器人绕行的动力。利用Matlab进行了仿真实验,将改进的AG算法和几种其他动态路径规划方法进行了对比。改进后的AG算法使机器人能够迅速躲避动态障碍物,有效地进行动态避障。研究方法不仅可以解决动态环境中机器人躲避动态障碍物并到达目标点的问题,而且与其他动态路径规划算法相比,具有路径长度更短、耗时更少、路径更平滑等优点。

关 键 词:计算机仿真  移动机器人  路径规划  动态环境  改进AG算法  动态避障
收稿时间:2018/3/14 0:00:00
修稿时间:2018/4/16 0:00:00

Robot dynamic path planning method based on improved AG algorithm
WANG Nan,ZHANG Jun and XIE Peng.Robot dynamic path planning method based on improved AG algorithm[J].Hebei Journal of Industrial Science & Technology,2018,35(3):178-184.
Authors:WANG Nan  ZHANG Jun and XIE Peng
Abstract:In order to make full use of the superiority of Agoraphilic(AG) algorithm, and make it be used for path planning in dynamic environment, the traditional AG algorithm is studied and improved. The relative velocity component between robot and dynamic obstacles is added when calculating the free space force. The component can be decomposed into two directional forces: one force moves the robot away from obstacles, and the other force moves the robot in the direction perpendicular to the obstacle and acts as a motive force for the robot to walk around. Simulation experiments are performed by using Matlab, and the improved AG algorithm is compared with several other dynamic path planning methods. The improved AG algorithm can help the robot avoid the dynamic obstacle rapidly, effectively avoiding dynamic obstacles. The improved AG algorithm can not only can solve the problem that a robot avoids dynamic obstacles and reach the target point in dynamic environment, but also has the advantages of shorter path length, less cost time and smoother path than other dynamic path planning algorithms.
Keywords:computer simulation  mobile robot  path planning  dynamic environment  improved AG algorithm  dynamic obstacle avoidance
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