Optimized Search Direction Based A-Star and DWA Fusion Algorithm for Path Planning of Automated Guided Vehicle

The traditional A-Star algorithm has defects of traversing a large number of nodes, low efficiency of algorithm operation, and unsmooth generated paths when solving the path planning problem of Automated Guided Vehicle.Therefore, this paper proposes optimized search direction based A-Star and Dynamic Window Approach(DWA). First, the search direction of A-Star algorithm is optimized, and an adaptive heuristic function is designed according to the different probabilities of obstacles on the path, in order to reduce the number of traversal nodes and improve the search efficiency of algorithm. Then, the removal strategy of redundant nodes is studied to smooth the path generated through A-Star algorithm, and by combining the advantages of the two algorithms of A-Star and DWA, a fusion algorithm is proposed, to adapt to the environment with the presence of static and dynamic obstacles and accomplish the purpose of path planning. Finally, the simulation is carried in the raster map generated by Matlab, and results show that the proposed algorithm in this paper has better global path planning and local dynamic obstacle avoidance.