A Spatiotemporal Framework for Cooperative Path Planning of Multi-UGV-UAV Delivery Systems
Yu-Hong Tan, Xingyao Han, Zhe Liu · 2025
In modern intelligent logistics systems, Multi-UGV-UAV Delivery Systems are pivotal in achieving last-mile delivery. Among their critical challenges, cooperative path planning between multiple UGVs and UAVs is critical to enhancing efficiency. Existing approaches face significant issues, including inefficient spatial resource utilization and prolonged waiting times for various vehicles. Moreover, the rendezvous between UGVs and UAVs exacerbates these inefficiencies, potentially leading to flight failures. To address these challenges, we propose a spatiotemporal search-based cooperative path planning framework, which significantly enhances spatial utilization between UGVs and UAVs, reducing congestion and deadlock between them. And it is complemented by a novel rendezvous mechanism for UGVs and UAVs, which ensures safe operations while significantly reducing the waiting time for UAVs and UGVs during rendezvous, thereby improving task execution efficiency. Experimental results on a widely used benchmark simulator in the industry demonstrate that our method outperforms existing approaches, achieving an approximately 20% improvement in task execution efficiency.