An integrated UGV-UAV cooperative navigation framework is proposed to support multiple unmanned ground vehicles (UGVs) operating with limited onboard perception. In this system, a LiDAR-equipped unmanned aerial vehicle (UAV) autonomously explores unknown environments and builds a global occupancy map through simultaneous localization and mapping (SLAM). The UGVs, lacking their own perception capabilities, rely on external motion capture systems for precise localization and receive the shared map information from the UAV to perform trajectory planning with obstacle avoidance. To ensure safe and efficient navigation, the UAV dynamically assesses potential collision risks along UGV-predicted paths and provides targeted perception support by visiting critical areas. A vehicle routing problem with time windows (VRPTW) model is formulated to optimize the UAV’s assistance schedule. The framework is validated through real-world indoor experiments, demonstrating its efficacy in enabling reliable multi-UGV navigation under constrained sensing conditions. The proposed system is particularly well-suited for structured environments such as warehouses, laboratories, and testbeds.