A dynamic path planning approach for dense, large, grid-based automated guided vehicle systems
K.J.C. Fransen, J.A.W.M. van Eekelen, A. Pogromsky, Marko Boon, Ivo Adan
Abstract
Real-time path planning for large, dense grid-based automated guided vehicle (AGV) systems, used for example to sort parcels, is challenging. Most approaches described in the literature are not fast enough for real-time control or are not able to avoid congestion. This paper presents a dynamic approach using a graph-representation of the grid system layout with vertex weights that are updated over time. By means of an extensive discrete-event simulation, we show that the proposed path planning approach significantly increases the throughput compared to existing approaches. Furthermore, it enables the recovery from deadlock situations.
Topics & Concepts
Computer scienceGridMotion planningsortRepresentation (politics)Path (computing)Distributed computingReal-time computingVertex (graph theory)DeadlockOccupancy grid mappingGraphThroughputTheoretical computer scienceArtificial intelligenceRobotMobile robotDatabaseMathematicsLawPolitical scienceGeometryTelecommunicationsPoliticsProgramming languageWirelessAdvanced Manufacturing and Logistics OptimizationRobotic Path Planning AlgorithmsOptimization and Search Problems