In this study, we aim to enhance the productivity and utilization of robots in construction sites by developing an optimal route planning system for autonomous mobile robots. The system generates lightweight graph-based maps from BIM and city models, enabling rapid pathfinding in large environments like university campuses. It maintains map data on a server and distributes route information via a web API. Validation with wheeled robots, humanoid robots, and drones confirmed efficient execution of point-to-point, multi-point, and detour routes. Updating server-stored map data improved route planning efficiency. Future work will focus on incorporating dynamic information to further enhance pathfinding.
