基于象限判别下的改进A^*算法路径规划

On the Improved Path Planning of A^*Algorithm Based on Quadrant Discrimination

传统A^*算法找到零碰撞概率的节点,需要很多处理时间并涉及检查很多相邻节点,因此工作效率较低。文章提出,将图像处理技术与路径规划避免碰撞技术相结合,通过基于象限判别下的改进A^*算法,识别从起始点到目标点的最佳路径,避免碰到任何障碍物。为了验证所提出的改进A^*算法可以解决传统A^*算法中的缺点,通过编程语言MATLAB的图形处理进行了避障路径仿真。结果表明,所提出的改进A^*算法可以有效缩短路径,减少处理时间。

Traditional A^*algorithms find nodes with zero collision probability that require a lot of processing time and involve checking of many neighboring nodes,and are therefore less efficient.The article proposes to combine image processing techniques with path planning collision avoidance techniques to identify the optimal path from the start point to the target point and avoid any obstacles through an improved A^*algorithm based on quadrant discrimination.In order to verify that the proposed improved A^*algorithm addresses the shortcomings of the traditional A^*algorithm,obstacle path simulation is performed by graphical processing in the programming language MATLAB.The results show that the proposed improved A^*algorithm can effectively shorten the path and reduce the processing time.