Dynamic chain for scheduling of the multi-AGV systems with load-aware motion profiling

In dynamic warehouse environments, conventional multi-AGV systems would adopt fixed-motion planning that does not take into account the physical constraints of vehicles and products, and therefore results in random collisions and inefficient routing. In order to deal with this, this investigation introduces a novel two-stage scheduling approach for ensuring sustainable and collision-free AGV coordination. First, the Dynamic Traveling Time estimation for AGV (DTT-AGV) algorithm estimates real travel times among neighbouring nodes accounting for acceleration, deceleration, and load conditions. Second, the Arrival Time Chaining for AGV path (ATC-AGV) scheme schedules dynamically the arrival time of each AGV at future nodes based on real-time system states and minimum safe-distance conditions to avoid conflicts. Both methods are validated on a grid-based warehouse layout with a hybrid simulation framework integrating kinematic modelling and system-level control. From these experiments, its results demonstrate that our innovative approach increases time accuracy, reduces tracking errors, and ensures safety in multi-AGV operation conditions. This method possesses practical value for scalable deployment in logistics and smart manufacturing systems.