马尔可夫性在AGV全局路径规划中的应用

通过对现有环境模型和路径规划算法的分析,提出了新的环境建模方法和基于已知环境信息的全局路径规划算法。对FMS采用机床位姿增广阵(APMM)和机床相对位姿阵(RPMM)进行建模,所建模型具有环境信息存储量小,数据易维护、易扩充等优点。最优路径的规划采用概率选择法,路径结点并行选择;最优路径取最大概率路径,路径规划效率高。仿真结果表明,所提出的路径规划算法具有简单、快速、可靠、并行搜索等优点。

Application of Markov in Global Path Planning of AGV

Through the analysis of the existing environment models and path planning algorithms,this paper suggests the new environment modelling method and the global path planning algorithm based on the known environment information.As to FMS,augmented pos matrix of machine and relative pos matrix of machines are used to carry out the model building.The constructed model is characterized by small storage of environment information,easy maintenance and expansion of data,etc.The probability selection method and the path junction point parallel selection are used to obtain the optimal path.The optimal path can take the maximum probability path so that the path planning is of high proficiency.The simulation results indicate that the suggested path planning algorithm is characterized by simplicity,fastness,reliability and parallel search,etc.