Decision graph for timely delivery of multi-AGVs in healthcare environment

The availability of Automated Guided Vehicles (AGVs) in flexible manufacturing systems is becoming the norm. However, in human-aware environments, e.g. healthcare environments, the movement of both AGVs and humans would inflict mutual harm. To reduce the harmfulness and the earliness/tardiness of ill-timed arrivals, a centralized control system needs to not only forecast the forthcoming traffic situation but also avoid abusing the emergency mode of AGVs. We propose a decision graph to reflect geometric topology and the ongoing traffic situation in the environment. This graph also allows the centralized control system to decide which AGV will be in emergency mode. Given this graph and a chosen regular shortest-path algorithm, the system could find out the best paths for AGVs to finish timely delivery and mitigate harmful effects on humans.