An Active Search Strategy with Multiple Unmanned Aerial Systems for Multiple Targets

TL;DR

This paper presents a novel multi-UAV active search strategy that combines global and local information, employs Voronoi partitioning for decentralized control, and demonstrates efficiency in ecological target search scenarios.

Contribution

It introduces an integrated search method with trajectory generation and Voronoi-based cooperation, improving multi-UAV search efficiency in natural environments.

Findings

Effective in reducing redundant movements

Demonstrated superior search efficiency in experiments

Applicable to ecological surveys and conservation

Abstract

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.