Cooperation-Aided Accurate UAV-Based LiDAR Mapping: Experimental Assessment

This paper presents results of an experimental activity conducted to prove the feasibility of using cooperation among Unmanned Aerial Vehicles to improve the geolocalization accuracy in Light Detection and Ranging (LiDAR)-based mapping applications. A chief-deputies architecture is considered, where the navigation state of the chief platform (which is embarking the LiDAR payload) is estimated by fusing measurements of its onboard Inertial Measurement Unit (IMU) and Global Navigation Satellite System (GNSS) receiver, with IMU-independent attitude measurements obtained by exploiting cooperation with the deputy platforms. Specifically, the chief attitude is computed by tightly integrating visual- and Carrier-phase Differential GNSS (CDGNSS) measurements of the chief-deputies directions in body and local coordinates, respectively, in the correction step of an extended Kalman filter. An experimental flight test has been conducted in a powerline mapping scenario to assess the performance of this cooperative technique in providing accurately geolocalized data. The experimental setup includes the following items: one customized DJI M300 platform (acting as chief) equipped with a Livox MID-40 LiDAR (mapping payload) and a fisheye camera (cooperative visual sensor); and two customized DJI M100 platforms acting as deputies. The three platforms are also equipped with GNSS receiver with raw data capability to enable CDGNSS processing. Results demonstrate an ability of reconstructing powerlines with a 0.42m Root Mean Square dispersion of the geolocalized points.