In this paper,based on the adjacency matrix of the network and its powers,the formulas are derived for theshortest path and the average path length,and an effective algorithm is presented.Furthermore,an example is pro...In this paper,based on the adjacency matrix of the network and its powers,the formulas are derived for theshortest path and the average path length,and an effective algorithm is presented.Furthermore,an example is providedto demonstrate the proposed method.展开更多
Path planning is important in the research of a mobile robot (MR). Methods for it have been used in different applications. An automated guided vehicle( AGV) , which is a kind of MR, is used in a flexible manufact...Path planning is important in the research of a mobile robot (MR). Methods for it have been used in different applications. An automated guided vehicle( AGV) , which is a kind of MR, is used in a flexible manufacturing system (FMS). Path planning for it is essential to improve the efficiency of FMS. A new method was proposed with known obstacle space FMS in this paper. FMS is described by the Augmented Pos Matrix of a Machine ( APMM ) and Relative Pos Matrix of Machines ( RPMM), which is smaller. The optimum path can be obtained according to the probability of the path and the maximal probability path. The suggested algorithm of path planning was good performance through simulation result: simplicity, saving time and reliability.展开更多
基金National Natural Science Foundation of China under the Key Project under Grant Nos.10635040 and 60774073the Natural Science Foundation of Jiangsu Province of China under Grant No.BK2007075
文摘In this paper,based on the adjacency matrix of the network and its powers,the formulas are derived for theshortest path and the average path length,and an effective algorithm is presented.Furthermore,an example is providedto demonstrate the proposed method.
文摘Path planning is important in the research of a mobile robot (MR). Methods for it have been used in different applications. An automated guided vehicle( AGV) , which is a kind of MR, is used in a flexible manufacturing system (FMS). Path planning for it is essential to improve the efficiency of FMS. A new method was proposed with known obstacle space FMS in this paper. FMS is described by the Augmented Pos Matrix of a Machine ( APMM ) and Relative Pos Matrix of Machines ( RPMM), which is smaller. The optimum path can be obtained according to the probability of the path and the maximal probability path. The suggested algorithm of path planning was good performance through simulation result: simplicity, saving time and reliability.