AGV path planning based on an improved A?algorithm
The A∗algorithm is a common AGV path planning algorithm,but the efficiency of the A∗ algorithm will be significantly reduced when the AGV movement environment is complex.In order to solve the problems of low path search efficiency and many path turns in the traditional A∗algorithm,an improved A∗algorithm is pro-posed.Firstly,the map is modeled based on the raster method,and then the heuristic function and neighborhood search strategy of the A∗algorithm are studied,the dynamic weighting mechanism is introduced to improve the heuristic function,and the dynamic five-neighborhood search strategy is added on this basis.Finally,in the python programming environment,two raster maps with different obstacle rates are used to compare and simulate the improved A∗algorithm and the traditional A∗algorithm.The simulation results show that the search time of the improved A∗algorithm is shortened by 69.3%on average,and the number of path expansion nodes is re-duced by 74.5%on average,which can significantly reduce the number of turns and improve the overall effi-ciency,especially when the obstacle rate is high.When Bezier curves are introduced,the movement path is smoother.
AGVpath planningimproved A∗algorithmdynamic weightingsearch for neighborhoodsBezier curves
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