Sorting Robots Cluster Evacuation Based on Deep Q Network and Danger Potential Field

This paper presents a solution to improve the evacuation efficiency of the sorting robot and the chances to preserve more assets in an emergency. We propose a danger potential field model for the intelligent sorting warehouse, which takes the number of AGVs between the grid and the exit into account. By taking the danger map calculated by the model as prior knowledge, the paper combines it with Deep Q Network to obtain an effective evacuation scheduling strategy. Finally, comparing the performance of the strategy with the performance of traditional automata and danger potential field in a visual simulator based on the real sorting warehouse using Pygame, the effectiveness and practicability of the model in the paper is verified.