Abstract
Recently, heterogeneous robots have been adopted in the same warehouse to enhance flexibility and improve system efficiency. Our paper is inspired by a novel heterogeneous robotic warehouse system, namely the lift robot and the ground robot collaborative (LRGR) warehousing system. In the LRGR system, lift robots store and retrieve totes on single deep storage racks. Meanwhile, ground robots transport totes between lift robots and workstations, navigating both the aisles and the space beneath the racks. The performance of an LRGR system is predominantly determined by its operational policies, especially the dwell point and junction point policies that regulate the interactions between lift and ground robots. We propose a fork-join queueing network to assess the performance of LRGR systems under various collaboration policies. An improved matrix-based approximation method is proposed to solve the model. The accuracy of the analytical models is verified by simulation. Our numerical experiments show that implementing the service completion junction point policy in combination with the service completion dwell point policy significantly boosts system efficiency and reduces energy consumption. Our model can provide new perspectives on effective collaboration policies for heterogeneous robotic systems.
