摘要
针对机器人静态路径规划全局最优的问题,提出了一种融合A*算法和势场法的全局路径规划方法。采用分层规划的思想逐层优化,首先利用改进A*算法规划得到基础的全局路径,接着对栅格细分并结合势场法提高路径规划的精度和安全裕度,在此基础上提出了一种去除多余节点的方法减小路径总长和总转向角,最后对得到的路径应用折线平滑方法进行优化处理得到一条光滑的路径曲线。文章以MATLAB为平台进行仿真,对所设计的路径规划方法进行测试,实验结果表明:与传统A*算法相比,改进的算法所规划的路径更短,更加平滑和安全,有利于机器人的运动控制。
This paper proposes a global path planning method combining A Star algorithm and potential field method, aiming at the optimal problem. Adopting the idea of hierarchical planning to optimize layer-by-layer.First use the improved A Star algor- ithra to plan to get the basic global path. Then subdivide the grid and combine the potential field method to improve the accuracy and safety margin of the path. Based on this, a method to remove redundant nodes is proposed to reduce the total path length and total steering angle. Finally, apply the polyline smoothing method for optimization to get a smooth final path. This article uses MATLAB as a platform to test the designed path planning method.The results show that compared with the traditional A Star algorithm, the improved algorithm has a shorter, smoother and safer path, and is beneficial to the robot＇s control.
出处
《信息通信》
2018年第6期17-20,23,共5页
Information & Communications
关键词
分层规划
A＊算法
势场法
路径平滑
Hierarchical programming
A Star algorithm
Potential field method
Path smoothing
