SOAR: Simultaneous Exploration and Photographing with Heterogeneous UAVs for Fast Autonomous Reconstruction
Mingjie Zhang, Chen Feng, Zengzhi Li, Guiyong Zheng, Yiming Luo, Zhu, Wang, Jinni Zhou, Shaojie Shen, and Boyu Zhou

TL;DR
SOAR is a multi-UAV system combining LiDAR and visual sensors, employing exploration and optimized viewpoint planning to enable fast, autonomous scene reconstruction in complex environments.
Contribution
The paper introduces a novel heterogeneous UAV system with a frontier-based exploration and viewpoint optimization strategy for efficient autonomous reconstruction.
Findings
Outperforms classical methods in simulation benchmarks.
Efficiently explores complex environments with heterogeneous UAVs.
Achieves rapid scene surface reconstruction with optimized planning.
Abstract
Unmanned Aerial Vehicles (UAVs) have gained significant popularity in scene reconstruction. This paper presents SOAR, a LiDAR-Visual heterogeneous multi-UAV system specifically designed for fast autonomous reconstruction of complex environments. Our system comprises a LiDAR-equipped explorer with a large field-of-view (FoV), alongside photographers equipped with cameras. To ensure rapid acquisition of the scene's surface geometry, we employ a surface frontier-based exploration strategy for the explorer. As the surface is progressively explored, we identify the uncovered areas and generate viewpoints incrementally. These viewpoints are then assigned to photographers through solving a Consistent Multiple Depot Multiple Traveling Salesman Problem (Consistent-MDMTSP), which optimizes scanning efficiency while ensuring task consistency. Finally, photographers utilize the assigned viewpoints…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · 3D Surveying and Cultural Heritage · Advanced Vision and Imaging
