Gradient Field Based Order Assignment in AGV Systems

This research examines the feasibility of using a field-based approach, within the multi-agent system (MAS) paradigm, to achieve transport assignment in an automatic guided vehicle (AGV) system. In a field-based approach, transports emit fields into the environment. The AGV’s behavior consists of continuously combining received fields and following the gradient of these combined fields. This will guide towards pick locations of transports, much like a ball rolls towards a valley in a (continuously changing) mountainous landscape. To avoid multiple AGVs driving towards the same transport, AGVs emit repulsive fields. The AGVs continuously reconsider the situation of the environment and transport assignment is delayed until a pickup, which benefits the flexibility of the system. The field-based approach is implemented in the AGV simulator developed by the AgentWise task force and its performance is examined. Experiments indicate that the field-based approach outperforms a Contract Net based protocol on various performance measures, such as the average time a transport has to wait for execution and the throughput, and in various circumstances, such as a varying number of AGVs and transports in the system. However, limitations of the field-based approach include AGVs driving superfluous distance and an unequal distribution of wait times across different pick locations. Also, it is not feasible to control, predict or reason about the emergent system-wide behavior or to provide guaranteed reaction times. Additionally, the tuning of the parameters of the approach often proved to require a time consuming trail-and-error approach. Finally, it remains to be seen if the large amount of messages that are transmitted in the approach can be supported by a real-world AGV-system.