Application of AI to AGV control?agent control of AGVs

Automated Guided Vehicle (AGV) systems are complex to design and to implement. Inefficiencies become difficult to avoid or even to control. This paper presents the theory behind a novel agent based AGV controller that aims to control the flow of AGVs in an effective manner and, therefore, overcome the inefficiencies that can be found in complex designs. Agents are simple entities that interact with other agents to produce an emergent behaviour that is not explicitly programmed into them. The AGV controller presented uses agents as traffic managers to allow access to points and segments in the guide path. Each agent has a rule base that it uses to assess the enquiries that it receives from an AGV. Each enquiry is evaluated only at the smallest possible part of the guide path rather than the entire guide path. AGVs are then able to allocate segments and points on their paths depending on the result of each enquiry. Simulation experiments were used to test the controller and an overview is presented.