Performance Analysis of Multi-Tote Storage and Retrieval Autonomous Mobile Robot Systems through Agent-Based Simulation

Multi-tote storage and retrieval autonomous mobile robot systems are new automated picking systems that feature mobile robots able to simultaneously carry multiple totes, fostering high efficiency and easily scalable layouts. This paper proposes an agent-based simulation model to estimate their performance and a numerical study that offers new design insights. Results show that robots and picking stations' configuration have significant impact on system performance. Specifically, adopting robots with more numerous trays for storing totes and equipment for the simultaneous unloading/loading of multiple totes at picking stations yields a reduction in the number of robots required to meet a given makespan.