Precise positioning through a loosely-coupled sensor fusion of GNSS-RTK, INS and LiDAR for autonomous driving
Andreas Schütz, Daniela E. Sanchez-Morales, Thomas Pany
Abstract
In this paper we describe the integration done between GNSS-RTK/INS/LiDAR in a loosely coupled Kalman Filter in the context of autonomous driving applications. Specifically, we focus in the assessment of potential LiDAR updates by comparing the velocity profile obtained by the GNSS/INS integration solution and the LiDAR observations. The results from a test drive are shown to provide an insight of the advantages of using the LiDAR updates in GNSS denied environments.
Topics & Concepts
GNSS applicationsLidarKalman filterContext (archaeology)Computer scienceSensor fusionFocus (optics)Real-time computingRemote sensingExtended Kalman filterGlobal Positioning SystemGeographyArtificial intelligenceTelecommunicationsArchaeologyOpticsPhysicsRobotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor NetworksIndoor and Outdoor Localization Technologies