Accuracy evaluation of 3D lidar data from small UAV

A UAV (Unmanned Aerial Vehicle) with an integrated lidar can be an efficient system for collection of high-resolution and accurate three-dimensional (3D) data. In this paper we evaluate the accuracy of a system consisting of a lidar sensor on a small UAV. High geometric accuracy in the produced point cloud is a fundamental qualification for detection and recognition of objects in a single-flight dataset as well as for change detection using two or several data collections over the same scene. Our work presented here has two purposes: first to relate the point cloud accuracy to data processing parameters and second, to examine the influence on accuracy from the UAV platform parameters. In our work, the accuracy is numerically quantified as local surface smoothness on planar surfaces, and as distance and relative height accuracy using data from a terrestrial laser scanner as reference. The UAV lidar system used is the Velodyne HDL-32E lidar on a multirotor UAV with a total weight of 7 kg. For processing of data into a geographically referenced point cloud, positioning and orientation of the lidar sensor is based on inertial navigation system (INS) data combined with lidar data. The combination of INS and lidar data is achieved in a dynamic calibration process that minimizes the navigation errors in six degrees of freedom, namely the errors of the absolute position (x, y, z) and the orientation (pitch, roll, yaw) measured by GPS/INS. Our results show that low-cost and light-weight MEMS based (microelectromechanical systems) INS equipment with a dynamic calibration process can obtain significantly improved accuracy compared to processing based solely on INS data.