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Scan matching SLAM in underwater environments

This paper proposes a pose-based algorithm to solve the full simultaneous localization and mapping problem for autonomous underwater vehicle (AUV) navigating in unknown and possibly unstructured environments. The proposed method first estimates the local path traveled by the robot while forming the acoustic image (scan) with range data coming from a mono-beam rotating sonar head, providing position estimates for correcting the distortions that the vehicle motion produces in the scans. Then, consecutive scans are cross-registered under a probabilistic scan matching technique for estimating the displacements of the vehicle including the uncertainty of the scan matching result. Finally, an augmented state extended Kalman filter estimates and keeps the registered scans poses. No prior structural information or initial pose are considered. The viability of the proposed approach has been tested reconstructing the trajectory of a guided AUV operating along a 600 m path within a marina environment

This research work was partially sponsored by the Spanish project DPI2011-27977-C03-02 (COMAROB) and two European Commission’s Seventh Framework Program 2007-2013 Projects: ICT-248497 (TRIDENT) and Marie Curie PERG-GA-2010-276778 (Surf3DSLAM). The dataset was acquired with the help of the members (staff and students) of the Computer Vision and Robotics research group at the University of Girona

Institute of Electrical and Electronics Engineers (IEEE)

Director: Ministerio de Ciencia e Innovación (Espanya)
Autor: Mallios, Angelos
Ridao Rodríguez, Pere
Ribas Romagós, David
Hernàndez Bes, Emili
Data: 2014
Resum: This paper proposes a pose-based algorithm to solve the full simultaneous localization and mapping problem for autonomous underwater vehicle (AUV) navigating in unknown and possibly unstructured environments. The proposed method first estimates the local path traveled by the robot while forming the acoustic image (scan) with range data coming from a mono-beam rotating sonar head, providing position estimates for correcting the distortions that the vehicle motion produces in the scans. Then, consecutive scans are cross-registered under a probabilistic scan matching technique for estimating the displacements of the vehicle including the uncertainty of the scan matching result. Finally, an augmented state extended Kalman filter estimates and keeps the registered scans poses. No prior structural information or initial pose are considered. The viability of the proposed approach has been tested reconstructing the trajectory of a guided AUV operating along a 600 m path within a marina environment
This research work was partially sponsored by the Spanish project DPI2011-27977-C03-02 (COMAROB) and two European Commission’s Seventh Framework Program 2007-2013 Projects: ICT-248497 (TRIDENT) and Marie Curie PERG-GA-2010-276778 (Surf3DSLAM). The dataset was acquired with the help of the members (staff and students) of the Computer Vision and Robotics research group at the University of Girona
Format: application/pdf
Accés al document: http://hdl.handle.net/10256/10212
Llenguatge: eng
Editor: Institute of Electrical and Electronics Engineers (IEEE)
Col·lecció: info:eu-repo/semantics/altIdentifier/doi/10.1007/s10514-013-9345-0
info:eu-repo/semantics/altIdentifier/issn/0929-5593
info:eu-repo/grantAgreement/MICINN//DPI2011-27977-C03-02/ES/COMAROB: ROBOTICA COOPERATIVA MARINA PARA EL MAPEO ACUSTICO Y LA INTERVENCION/
info:eu-repo/grantAgreement/EC/FP7/276778/EU/Probabilistic 3D surface matching for bathymetry based Simultaneous Localization and Mapping of underwater vehicles/SURF3DSLAM
info:eu-repo/grantAgreement/EC/FP7/248497/EU/Marine Robots and Dexterous Manipulation for Enabling Autonomous Underwater Multipurpose Intervention Missions/TRIDENT
Drets: Tots els drets reservats
Matèria: Robots mòbils
Mobile robots
Robots autònoms
Autonomous robots
Vehicles submergibles
Submersibles
Fons marins -- Mapes
Ocean bottom -- Maps
Títol: Scan matching SLAM in underwater environments
Tipus: info:eu-repo/semantics/article
Repositori: DUGiDocs

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