Next Article in Journal
An Image Stabilization Optical System Using Deformable Freeform Mirrors
Previous Article in Journal
An X-Band Radar System for Bathymetry and Wave Field Analysis in a Harbour Area
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(1), 1708-1735;

Trajectory-Based Visual Localization in Underwater Surveying Missions

System, Robotics and Vision Group, Department Matemàtiques i Informàtica, Universitat de les Illes Balears, Ctra. Valldemossa, Km. 7.5, 07122 Palma de Mallorca, Spain
Author to whom correspondence should be addressed.
Received: 27 October 2014 / Accepted: 31 December 2014 / Published: 14 January 2015
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [2110 KB, uploaded 14 January 2015]


We present a new vision-based localization system applied to an autonomous underwater vehicle (AUV) with limited sensing and computation capabilities. The traditional EKF-SLAM approaches are usually expensive in terms of execution time; the approach presented in this paper strengthens this method by adopting a trajectory-based schema that reduces the computational requirements. The pose of the vehicle is estimated using an extended Kalman filter (EKF), which predicts the vehicle motion by means of a visual odometer and corrects these predictions using the data associations (loop closures) between the current frame and the previous ones. One of the most important steps in this procedure is the image registration method, as it reinforces the data association and, thus, makes it possible to close loops reliably. Since the use of standard EKFs entail linearization errors that can distort the vehicle pose estimations, the approach has also been tested using an iterated Kalman filter (IEKF). Experiments have been conducted using a real underwater vehicle in controlled scenarios and in shallow sea waters, showing an excellent performance with very small errors, both in the vehicle pose and in the overall trajectory estimates. View Full-Text
Keywords: underwater robotics; visual localization; data association; image registration underwater robotics; visual localization; data association; image registration
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Burguera, A.; Bonin-Font, F.; Oliver, G. Trajectory-Based Visual Localization in Underwater Surveying Missions. Sensors 2015, 15, 1708-1735.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top