Warehouses with heterogeneous robots collaboration: operational policies and performance analysis
研究了异构自主移动机器人协作仓储系统的运营策略，通过排队网络模型分析性能，发现机器人分配和存储策略对吞吐时间有显著影响。
The novel heterogeneous autonomous mobile robots collaborative storage and retrieval systems (H-AMRs systems), now widely adopted, feature collaboration between bin picker (BP) and bin mover (BM) autonomous mobile robots. In these systems, BP robots retrieve bins from storage locations and lower them to buffer areas beneath the storage racks, where BM robots then transport the bins to picking stations for order fulfilment. The intricate interaction between these two types of robots significantly complicates the evaluation and analysis of system performance and operational policies. This paper pioneers research on H-AMRs systems by developing a multi-class nested queuing network model to estimate system performance. Numerical experiments indicate that reshuffling policies have minimal impact on throughput time due to the distinct relay between BP and BM robots, and deploying 10 additional BP robots and 3 additional BM robots beyond the minimum required quantities proves cost-efficient. Assigning BP robots to specific aisles reduces throughput time by up to 26.1%; compared to shared assignments under a sufficient budget. Moreover, when BP robots share aisle assignments, the optimal storage policy depends on the warehouse layout. Conversely, with aisle-specific assignments for BP robots, a zoned storage policy aligned with aisle direction consistently optimises performance, regardless of the warehouse layout.