A fuzzy logic expert system for the automated generation of roadmaps for automated guided vehicle systems

So far the generation of roadmaps for automated guided vehicles (AGVs) is mostly performed manually. Mathematical path finding algorithms often return results that are mathematically optimal but not applicable to a real production layout. This paper proposes an expert system as a solution that combines traditional path finding algorithms (in the form of a modified version of the A* and the Bellman-Ford algorithm) with a fuzzy inference system that incorporates the human knowledge of AGV system planners. Results that prove the efficiency of the proposed solution are shown in the end.