Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

Angelos Mallios, Pere Ridao, Emili Hernández, David Ribas, Francesco Maurelli, Yvan Petillot

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Citations (Scopus)


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 600m path within a marina environment, showing the viability of the proposed approach. ©2009 IEEE.

Original languageEnglish
Title of host publicationOCEANS '09 IEEE Bremen: Balancing Technology with Future Needs
ISBN (Electronic)978-1-4244-2523-5
ISBN (Print)978-1-4244-2522-8
Publication statusPublished - 11 May 2009
EventOCEANS 2009 - Bremen, Germany
Duration: 11 May 200914 May 2009


ConferenceOCEANS 2009
OtherBalancing technology with future needs


Dive into the research topics of 'Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar'. Together they form a unique fingerprint.

Cite this