2026-04-13T07:14:35Zhttps://recercat.cat/oai/request

oai:recercat.cat:10256/21602024-05-22T09:46:38Zcom_2072_452955com_2072_2054col_2072_452957

00925njm 22002777a 4500 dc Mallios, Angelos author Ridao Rodríguez, Pere author Hernàndez Bes, Emili author Ribas Romagós, David author Maurelli, Francesco author Petillot, Yvan R. author 2009 This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach http://hdl.handle.net/10256/2160 Robots mòbils Robots mòbils -- Sistemes de control Vehicles submergibles -- Sistemes de control Vehicles submergibles -- Telecontrol Mobile robots Mobile robots -- Control systems Submersibles -- Control systems Submersibles -- Remote control Algorismes computacionals Computer algorithms Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar