  Path planning in the multi-robot system refers to calculating a set of
actions for each robot, which will move each robot to its goal without
conflicting with other robots. Lately, the research topic has received
significant attention for its extensive applications, such as airport ground,
drone swarms, and automatic warehouses. Despite these available research
results, most of the existing investigations are concerned with the cases of
robots with a fixed movement speed without considering uncertainty. Therefore,
in this work, we study the problem of path-planning in the multi-robot
automatic warehouse context, which considers the time-varying and uncertain
robots' movement speed. Specifically, the path-planning module searches a path
with as few conflicts as possible for a single agent by calculating traffic
cost based on customarily distributed conflict probability and combining it
with the classic A* algorithm. However, this probability-based method cannot
eliminate all conflicts, and speed's uncertainty will constantly cause new
conflicts. As a supplement, we propose the other two modules. The conflict
detection and re-planning module chooses objects requiring re-planning paths
from the agents involved in different types of conflicts periodically by our
designed rules. Also, at each step, the scheduling module fills up the agent's
preserved queue and decides who has a higher priority when the same element is
assigned to two agents simultaneously. Finally, we compare the proposed
algorithm with other algorithms from academia and industry, and the results
show that the proposed method is validated as the best performance.
