Dynamic multi-agent pickup and delivery under communication uncertainties in robotic cellular warehousing systems

Robotic cellular warehousing systems (RCWS) represent a new paradigm for automated logistics, yet existing multi-agent pickup and delivery (MAPD) formulations typically assume static orders and ideal communication, which rarely hold in practice. This paper studies dynamic MAPD in RCWS under communication uncertainty for the first time, where order specifications may evolve during execution and coordination decisions rely on delayed information. To capture communication effects at the system level, we model uncertainty as location-dependent stochastic transmission delays using radio maps, which reflect spatial heterogeneity induced by warehouse layout and scale. Based on this model, we develop a communication-aware token-passing framework that adapts replanning decisions to both the timing and spatial context of received updates, enabling effective coordination under non-ideal information exchange. Extensive simulations under varying order dynamics, robot fleet sizes, and communication conditions demonstrate that coordination strategies designed for static and delay-free settings can degrade significantly in uncertain environments. The results further reveal fundamental trade-offs between responsiveness and resource utilization, and show that exploiting idle resources through cooperative coordination can substantially improve system performance. These findings highlight the critical role of communication in dynamic warehouse operations and provide practical guidance for designing coordination policies and system configurations in RCWS.