Robotic Sorting Systems: Robot Management and Layout Design Optimization

TL;DR

This paper introduces a novel traffic management method for robotic sorting systems that improves throughput and reduces service time, and develops an optimized layout model considering costs and throughput for small-scale warehouse operations.

Contribution

It presents the RC-S traffic management approach and a layout optimization model that jointly enhance system performance and cost-efficiency in robotic sorting systems.

Findings

RC-S reduces average service time by 10.3% compared to classical algorithms.

System throughput and runtime are improved with RC-S.

Optimal layout depends on throughput levels, with costs shifting from facility to labor at higher throughput.

Abstract

In the contemporary logistics industry, automation plays a pivotal role in enhancing production efficiency and expanding industrial scale. Autonomous mobile robots, in particular, have become integral to the modernization efforts in warehouses. One noteworthy application in robotic warehousing is the robotic sorting system (RSS), distinguished by its characteristics such as cost-effectiveness, simplicity, scalability, and adaptable throughput control. While previous research has focused on analyzing the efficiency of RSS, it often assumed an ideal robot management system ignoring potential queuing delays by assuming constant travel times. This study relaxes this assumption and explores the quantitative relationship between RSS configuration parameters and system throughput. We introduce a novel robot traffic management method, named the rhythmic control for sorting scenario (RC-S), for RSS operations, equipped with an estimation formula establishing the relationship between system performance and configurations. Simulations validate that RC-S reduces average service time by 10.3\% compared to the classical cooperative A* algorithm, while also improving throughput and runtime. Based on the performance analysis of RC-S, we further develop a layout optimization model for RSS, considering RSS configuration, desired throughput, and costs, to minimize expenses and determine the best layout. Numerical studies show that at lower throughput levels, facility costs dominate, while at higher throughput levels, labor costs prevail. Additionally, due to traffic efficiency limitations, RSS is well-suited for small-scale operations like end-of-supply-chain distribution centers.