A Scalable Sensor Fusion Framework for the Localization of a Vehicle on Detailed Digital Maps Using Laserscanners

Robust ego-localization is an essential technology for future intelligent vehicles and cooperative systems. In this paper a multi sensor fusion framework for the precise estimation of the position, the orientation as well as the velocity and the yaw rate of a vehicle is proposed. Therefore, the data of different sensor systems is combined, such as laser scanners, high accuracy digital maps, GPS and the on-board sensors of the vehicle. In order to improve the accuracy of the position and the orientation estimation, stationary objects, such as posts of traffic lights and traffic signs as well as house walls are registered in detailed digital maps and are used as landmarks, which are detected by an automotive laser scanner. With known positions of the landmarks in the laser scan, the position and orientation of the vehicle are precisely estimated. The scalable architecture also supports any other position measurement systems