Dataset for positioning and tracking cars and pedestrians from uav imagery and static lidar

Abstract. The development of autonomous vehicles, both terrestrial and aerial ones (unmanned aerial system (UAS)), is causing the need of properly formulating appropriate solutions for ensuring a safe interaction between them, human beings and the infrastructures and environment in their operating area. To such aim, the knowledge of the positions of different platforms moving in the considered area is fundamental. GNSS (Global Navigation Satellite System) is by far the most used positioning technique in order to determine positions all over the world. Nevertheless, there are several conditions in which its use is unfortunately impossible or unreliable. Hence, different techniques, based on the use of sensors either mounted on the moving platforms or on an ad-hoc infrastructure, shall be used in order to determine the absolute and relative positions of the involved platforms. To this aim, this work proposes the use of vision, in particular from UAS imagery, static LiDAR (Light Detection and Ranging) and UWB (Ultra Wide-Band) transceivers, with initial encouraging results.