Kolloquium Geoinformatik Mobile Mapping with SLAM

Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. In this talk, we present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors including vehicle odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm from the robotics community the temporary failure of accurate external positioning systems or the lack thereof can be compensated for.
We demonstrate the capabilities of the proposed algorithms on a wide variety of data sets, including a backpack mounted mobile mapping system and a sensor skid for digitizing production lines.