Angelos Mallios defends his PhD Thesis “Sonar Scan Matching for Simultaneous Localization and Mapping in Confined Underwater Environments”
This thesis presents the development of a localization and mapping algorithm for an autonomous underwater vehicle (AUV). It is based on probabilistic scan matching of raw sonar scans within a pose-based simultaneous localization and mapping (SLAM) framework. To address the motion-induced distortions affecting the generation of full sector scans, an extended Kalman filter (EKF) is used to estimate the robot motion during that scan. The filter uses a constant velocity model with acceleration noise for motion prediction.Velocities from Doppler velocity log (DVL) and heading measurements from attitude and heading reference system (AHRS) are fed asynchronously and update the state….