LiDAR Observations by Motion Compensation and Scan Accumulation

In dynamic localization problems, the observations used from exteroceptive sensors are usually obtained from a single measurement. However, there are cases where the current measurement is not sufficient to detect the referenced landmark or to get a sufficient level of accuracy. In this study, a point cloud accumulation strategy is used to improve the resolution of a LiDAR sensor along its sparse axis. In particular, we are interested in the detection of markings transverse to the road axis in order to improve the accuracy of localization of an autonomous vehicle when approaching intersections or roundabouts. We present a method that allows the construction of an accurate observation with an associated observation model based on a High-Definition (HD) map through an accumulation of scans as the vehicle moves, by compensating the vehicle motion. The parameters of the accumulator are studied in terms of detection and accuracy. The quality of the observations and their impact on the localization quality are analyzed using real experiments carried out with an experimental vehicle equipped with a low-cost GNSS receiver, dead-reckoning sensors and a ground truth system.