Workshop: Autonomous Guided Vehicles (AGVs)

Autonomous Guided Vehicles (AGVs) play a central role in modern logistics and manufacturing by enabling automated, flexible, and efficient material handling. To improve their reliability and adaptability, simulation modeling provides a powerful approach to design, test, and validate AGV path tracking strategies before real-world deployment. This keynote first introduces the fundamentals of AGVs and their applications in industrial environments, followed by a step-by-step explanation of how to develop simulation models for path tracking. Different modeling techniques are highlighted, including EF, EFM1, and fusion models, which provide scalable frameworks for analyzing AGV performance in complex layouts. The talk then explores two major classes of routing algorithms: station-to-station methods that rely on global cost matrices (e.g., Floyd-Warshall, Traveling Salesman Problem) and edge-based approaches that utilize predefined pathways and intermediate waypoints (e.g., Dijkstra, Depth-First Search, Kruskal’s Minimum Spanning Tree). By comparing these algorithmic strategies within simulation environments, we demonstrate how fusion models and optimized routing enhance efficiency, reduce congestion, and improve adaptability in dynamic settings. Finally, real testing results are discussed to bridge the gap between simulation and industrial application, showing how AGV simulation frameworks can accelerate deployment while reducing cost and risk. This integrated perspective provides researchers and practitioners with practical insights into AGV modeling, algorithm design, and industrial validation.