基于改进A-Star算法的AGV全局路径规划

AGV Global Path Planning Based on the Improved A-Star Algorithm

针对智能仓储物流AGV全局路径规划,提出了改进的A-Star算法。该算法在原有估价函数的基础上,引入惩罚函数和奖励因子,以解决传统A-Star算法拐点多的问题,进而提升AGV的全局运输效率。为评估改进算法的有效性,文章基于Visual Studio设计了Windows应用开发程序进行仿真实验。实验结果表明,改进的A-Star算法可显著降低AGV的转弯次数,有效提高AGV的运输效率。

Aiming at AGV global path planning in warehouse logistics,an improved A-Star algorithm is proposed. Based on the original valuation function,the algorithm introduces a penalty function and a reward factor to solve the problem of too many inflection points in the traditional A-Star algorithm,which can improve the transport efficiency of AGV. In order to evaluate the effectiveness of the improved algorithm,the Windows application program is designed for simulation experiments based on Visual Studio. The experimental results show that the improved A-Star algorithm can effectively reduce the number of turns of AGV and significantly improve the transport efficiency of AGV.