Traditionally, unmanned aerial vehicles (UAVs) rely on CMOS-based cameras to collect images about the world below. One of the most successful applications of UAVs is to generate orthomosaics or orthomaps, in which a series of images are integrated together to develop a larger map. However, the use of CMOS-based cameras with global or rolling shutters mean that orthomaps are vulnerable to challenging light conditions, motion blur, and high-speed motion of independently moving objects under the camera. Event cameras are less sensitive to these issues, as their pixels are able to trigger asynchronously on brightness changes. This work introduces the first orthomosaic approach using event cameras. In contrast to existing methods relying only on CMOS cameras, our approach enables map generation even in challenging light conditions, including direct sunlight and after sunset.

翻译：传统上，无人飞行器依赖基于CMOS的相机采集下方世界的图像。无人飞行器最成功的应用之一是生成正射影像或正射地图，即通过整合一系列图像构建更大范围的地图。然而，使用具有全局或卷帘快门的CMOS相机意味着正射地图易受挑战性光照条件、运动模糊以及相机下方独立运动物体的高速运动影响。事件相机对这些问题较不敏感，因其像素能够基于亮度变化异步触发。本研究首次提出了使用事件相机的正射影像生成方法。与仅依赖CMOS相机的现有方法相比，我们的方法能够在包括直射阳光和日落后在内的挑战性光照条件下实现地图生成。