基于栅格地图改进的智能路径选择算法

Improved intelligent path selection algorithm based on grid map

交通和物流领域的发展,对路径规划算法的时间复杂度与精度提出了越来越高的要求。针对该问题,提出了一种基于栅格地图改进的智能路径选择算法。该算法利用方向信息来对算法进行优化设计,基于原有地图带有的始末位置的方向信息,定义权值矩阵与方向权重向量,以此作为路径中下个栅格的选择依据,并采取奖励与惩罚措施来提高算法的收敛速度。此外,算法还采取了多余栅格的优化措施来提高算法性能。通过对于典型仓储AVG问题模型的仿真来验证算法的有效性。结果表明,路径长度收敛到满足条件的较优解所需的时间,智能路径选择算法较A;算法及传统Dijkstra算法可以减少10%以上,具有较低的时间复杂度和较高的寻优效率。

With the development of transportation and logistics, higher requirements are put forward for the time complexity and accuracy of path planning algorithm. Aiming at this problem, proposes an improved intelligent path selection algorithm based on grid map which uses the direction information to optimize the algorithm. Based on the direction information of the beginning and end positions in the original map, the weight matrix and direction weight vector are defined as the basis for the selection of the next grid in the path, and reward and punishment measures are taken to improve the convergence speed of the algorithm. In addition, the algorithm also takes the optimization measures of redundant grid to improve the performance of the algorithm. The effectiveness of the algorithm is verified by the simulation of a typical storage AVG problem model. Simulation results show that the time required for the path length to converge to the optimal solution can be reduced by more than 10% compared with A;algorithm and traditional Dijkstra algorithm. The proposed intelligent path selection algorithm has lower time complexity and higher optimization efficiency as well.