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This paper tackles the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem, where a UGV is supported by UAVs to navigate uncertain road networks with potentially impassable edges. The study introduces multiple strategies, including a bidirectional approach, to enhance UGV-UAV cooperation for safe and efficient pathfinding, particularly in critical scenarios like disaster response. Results from evaluations on 100 urban road networks reveal that the bidirectional strategy consistently outperforms others, and employing multiple UAVs significantly reduces UGV travel time despite increased computation demands.
The bidirectional strategy for UGV-UAV cooperation not only optimizes pathfinding in uncertain environments but also demonstrates significant time savings when leveraging multiple UAVs.
This paper addresses the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem involving one unmanned ground vehicle (UGV) assisted by one or more unmanned aerial vehicles (UAVs) operating on an uncertain road network with potentially impassable edges. DUCPP is particularly relevant for scenarios such as disaster response, emergency supply transport, and rescue operations, where a UGV must reach a specified destination in the presence of partially unknown road conditions. To enable the UGV to travel safely and efficiently to its destination, the UAV(s) dynamically inspect edges in the environment to identify and prune damaged or impassable edges from consideration. We present multiple strategies, including a bidirectional approach, to optimize UGV-UAV cooperation for finding a safe path in an uncertain road network. Furthermore, we explore the impact of using multiple UAVs on reducing the UGV's travel time, and evaluate the associated computation time. The proposed strategies are implemented and evaluated on 100 urban road networks. The results demonstrate that the bidirectional strategy achieves the best performance in most instances, and using multiple UAVs further reduces UGV travel time at the expense of increased computation time. This paper presents a robust framework for DUCPP to achieve efficient UGV-UAV cooperation for path planning and inspection, offering practical solutions for navigation in challenging and uncertain conditions.
