A Timewindow-Based Multi-AGV Path Planning Method Using Improved A Star Algorithm

In the current smart warehouse system, AGVs need to complete goods transport tasks efficiently, requiring curve-less and conflict-free path planning in multi-AGV case to improve efficiency of the whole system. To solve above problems, based on an improved A star algorithm to generate initial paths, this paper adds an extra turning cost on paths to reduce curves. Then two kinds of timewindow detection are proposed to check if collision happens between AGVs. To avoid collision, we develop three path replanning methods to search more feasible paths efficiently according to task priority principal. The simulation experiments indicate that improved A star algorithm has an advantage in reducing curves in paths, and the timewindow-based method is capable of multi-AGV cases, realizing conflict-free path planning.