This work studies multi-robot navigation in multi-floor facilities equipped with elevators. The baseline model is Multi-Agent Path Finding (MAPF) in a discrete space-time environment, where each robot must reach its goal while avoiding vertex and edge conflicts. Unlike the classical single-floor MAPF setting, multi-floor warehouses include vertical transport resources (elevators) with limited throughput, nonzero travel time between floors, and cabin-presence constraints. In the existing literature, elevator-control tasks and MAPF tasks are usually considered separately: elevator papers do not account for detailed coordination of many mobile agents, while MAPF papers assume single-level geometry or simplified vertical transitions. This study focuses on an intermediate practical setting in which elevators are treated as resource agents inside a MAPF problem. We adapt and empirically evaluate priority-based cooperative planning algorithms under elevator-specific constraints, using reservation table mechanisms to coordinate both floor-level movement and elevator usage. The evaluation compares planners across different map structures, elevator placements, and agent loads, focusing on reliability, runtime, and path quality. The results provide an empirical view of how priority-based planners behave when vertical transport becomes a shared and constrained resource.
DOI: 10.1007/978-3-032-34387-1_22
Download the collection of works (PDF) from Springer Nature: https://link.springer.com/content/pdf/10.1007/978-3-032-34387-1.pdf
Medvedev, M., Dergachev, S., Yakovlev, K. (2027). Empirical Evaluation of Priority-Based Planners for Multi-agent Path Finding with Elevators // In: Ronzhin, A., Gribova, V., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2026. Lecture Notes in Computer Science, Vol. 16790, pp. 305–318.