万方, 周风余, 尹磊, 王玉刚, 陈科, 沈冬冬. 基于电势场法的移动机器人全局路径规划算法[J]. 机器人, 2019, 41(6): 742-750. DOI: 10.13973/j.cnki.robot.180687
引用本文: 万方, 周风余, 尹磊, 王玉刚, 陈科, 沈冬冬. 基于电势场法的移动机器人全局路径规划算法[J]. 机器人, 2019, 41(6): 742-750. DOI: 10.13973/j.cnki.robot.180687
WAN Fang, ZHOU Fengyu, YIN Lei, WANG Yugang, CHEN Ke, SHEN Dongdong. Global Path Planning Algorithm of Mobile Robot Based on Electric Potential Field[J]. ROBOT, 2019, 41(6): 742-750. DOI: 10.13973/j.cnki.robot.180687
Citation: WAN Fang, ZHOU Fengyu, YIN Lei, WANG Yugang, CHEN Ke, SHEN Dongdong. Global Path Planning Algorithm of Mobile Robot Based on Electric Potential Field[J]. ROBOT, 2019, 41(6): 742-750. DOI: 10.13973/j.cnki.robot.180687

基于电势场法的移动机器人全局路径规划算法

Global Path Planning Algorithm of Mobile Robot Based on Electric Potential Field

  • 摘要: 针对传统路径规划算法计算量大、电路映射地图建模复杂等问题,提出了一种基于电势场法的路径规划新方法.首先,为降低环境建模的复杂度,对Zhang细化算法进行了改进,获得能够细致描绘地图连通关系的骨干图;在此基础上,提出了一种基于电势场理论的模型建立方法,此后通过对模型电流通路的快速搜索获取初始路线,大大降低了路径规划算法的运算量;然后,基于内接圆角方法对路径进行平滑处理,解决了路径离散问题,得到适合服务机器人行走的最优路径.大量对比实验表明,该改进Zhang细化算法有效降低了建模及求解复杂度,提出的基于电势场法的全局路径规划算法很好地解决了传统算法搜索效率低的问题.

     

    Abstract: A new path planning method based on the electric potential field method is proposed aiming at the problems of large computation and complex circuit mapping modeling in traditional path planning algorithms. Firstly, in order to reduce the complexity of environment modeling, the improved Zhang thinning algorithm is used to obtain the backbone diagram, which can depict the connectivity of the map in detail. Secondly, based on the backbone diagram, a model building method based on the electric potential field theory is proposed, and the initial route is obtained by searching the current path of the model quickly, which greatly reduces the computational complexity of the path planning algorithm. Then, the path is smoothed based on the inner fillet method to get the optimal path for the service robot, solving the problem of path discretization. A large number of comparative experiments show that the improved Zhang thinning algorithm proposed effectively reduces the complexity of modeling and solving. The proposed global path-planning algorithm based on the electric potential field solves the problem of low search efficiency of traditional algorithms.

     

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