Multi-UAV adaptive cooperative coverage search method based on area dynamic sensing

Abstract

Traditional manual search for large-scale unknown areas is inefficient and hazardous, making multi-UAV (unmanned aerial vehicle) collaborative search a growing trend. However, existing methods still have shortcomings in complex environments or during sudden failures. This paper proposes a multi-UAV adaptive cooperative coverage search method based on area dynamic sensing. First, the search problem is modelled as an optimization problem, and a sensing set segmentation method is introduced along with performance metrics. Secondly, perception partitioning is used to avoid redundant detection, and dynamic path guidance technology drives the UAV swarm toward unexplored areas. Finally, an auction allocation task strategy is employed to plan optimal paths for each UAV in real-Time, and collision avoidance algorithms are improved to enhance safety. Experiments demonstrate that this method excels in coverage rate, interference resistance, and environmental adaptability.