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.
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