论文标题
合成孔径感测以用无人机群的遮挡去除
Synthetic Aperture Sensing for Occlusion Removal with Drone Swarms
论文作者
论文摘要
我们证明了在森林茂密的地区（例如在搜查和救援任务中失去的人）中检测和跟踪封闭的目标时，可以如何有效地自动无人机群。探索和优化局部观看条件（例如遮挡密度和目标视图倾斜），比以前基于预定义的路点的盲目采样策略提供了更快，更可靠的结果。提出了适应性的实时粒子群优化和新的目标函数，能够处理动态和高度随机的跨层条件。合成孔径传感是我们的基本采样原理，并且使用无人机群来近似具有极高且适应能力的机载镜头的光学信号。
We demonstrate how efficient autonomous drone swarms can be in detecting and tracking occluded targets in densely forested areas, such as lost people during search and rescue missions. Exploration and optimization of local viewing conditions, such as occlusion density and target view obliqueness, provide much faster and much more reliable results than previous, blind sampling strategies that are based on pre-defined waypoints. An adapted real-time particle swarm optimization and a new objective function are presented that are able to deal with dynamic and highly random through-foliage conditions. Synthetic aperture sensing is our fundamental sampling principle, and drone swarms are employed to approximate the optical signals of extremely wide and adaptable airborne lenses.
