  The challenge of efficient target searching in vast natural environments has
driven the need for advanced multi-UAV active search strategies. This paper
introduces a novel method in which global and local information is adeptly
merged to avoid issues such as myopia and redundant back-and-forth movements.
In addition, a trajectory generation method is used to ensure the search
pattern within continuous space. To further optimize multi-agent cooperation,
the Voronoi partition technique is employed, ensuring a reduction in repetitive
flight patterns and making the control of multiple agents in a decentralized
way. Through a series of experiments, the evaluation and comparison results
demonstrate the efficiency of our approach in various environments. The primary
application of this innovative approach is demonstrated in the search for
horseshoe crabs within their wild habitats, showcasing its potential to
revolutionize ecological survey and conservation efforts.
