核心概念
The author proposes a cost-effective strategy for heterogeneous UAV swarm systems to conduct cooperative aerial inspection, focusing on task allocation and exploration efficiency.
摘要
The content discusses a novel approach for cooperative aerial inspection using heterogeneous UAV swarm systems. The proposed method aims to optimize task assignment and exploration efficiency while minimizing costs. By partitioning agents into teams with different tasks, including mapping, exploration, and inspection, the method achieves superior performance in challenging experiments. The use of voxel map-based representation and rule-based path-planning enhances the approach's effectiveness in achieving full 3D surface coverage of objects. The research contributes to addressing the domain gap in autonomous exploration and inspection by introducing a robust and efficient solution based on heterogeneous drones.
統計資料
"We achieved the best performance in all challenging experiments with the proposed approach."
"The test environment size is 130m x 70m x 60m."
"Increasing the number of drones also means higher perceptions of overheads."
引述
"We propose a task assignment method for heterogeneous UAV swarms, incorporating high-end LiDAR mapping drones and lower-end drones for image capturing."
"Our main contributions are summarized below: We propose a task assignment method for heterogeneous UAV swarms..."
"The proposed method can complete inspection tasks under challenging conditions, such as limited communication..."