This paper outlines the specifications and basic design approach taken on the development of the Girona 500, an autonomous underwater vehicle whose most remarkable characteristic is its capacity to reconfigure for different tasks. The capabilities of this new vehicle range from different forms of seafloor survey to inspection and intervention tasks.

Girona 500 AUV: From Survey to Intervention

We have established an Australia-wide observation program that exhibits recent developments in autonomous underwater vehicle (AUV) systems to deliver precisely navigated time series benthic imagery at selected reference stations on Australia's continental shelf. These observations are designed to help characterize changes in benthic assemblage composition and cover derived from precisely registered maps collected at regular intervals. This information will provide researchers with the baseline ecological data necessary to make quantitative inferences about the long-term effects of climate change and human activities on the benthos. Incorporating a suite of observations that capitalize on the unique capabilities of AUVs into Australia's integrated marine observation system (IMOS) [1] is providing a critical link between oceanographic and benthic processes. IMOS is a nationally coordinated program designed to establish and maintain the research infrastructure required to support Australia's marine science research. It has, and will maintain, a strategic focus on the impact of major boundary currents on continental shelf environments, ecosystems, and biodiversity. The IMOS AUV facility observation program is designed to generate physical and biological observations of benthic variables that cannot be cost effectively obtained by other means.

Monitoring of Benthic Reference Sites: Using an Autonomous Underwater Vehicle

This paper presents an automated solution to the visual inspection problem of hydroelectric dams. A small autonomous underwater vehicle, controllable in four degrees of freedom (surge, sway, heave, and yaw), is used for autonomously exploring the wall of a dam. The robot is easily programmed using a mission control language. Missions are executed by an intelligent control architecture that guides the robot to follow a predefined path surveying the wall. During the mission, the robot gathers onboard navigation data synchronized with optical imagery, sonar, and absolute navigation data, obtained from a moored buoy equipped with an ultra-short baseline system. After the mission, the images of the wall are used to build a photomosaic of the inspected area. First, image features are matched over the image sequence. Then, navigation data and interimage correspondences are optimized together using bundle adjustment techniques. Thus, a georeferenced globally aligned set of images is obtained. Finally, a blending algorithm is used to obtain smooth seam transitions among the different images that constitute the mosaic, compensating for light artifacts and improving the visual perception of the scene. © 2010 Wiley Periodicals, Inc.

/pdf/visual-inspection-of-hydroelectric-dams-using-an-autonomous-3tkmdb5opx.pdf

Visual inspection of hydroelectric dams using an autonomous underwater vehicle

ReviewIntervention AUVs: The next challenge☆☆☆

Challenges and future trends in marine robotics

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported.

/pdf/large-area-photo-mosaics-using-global-alignment-and-39p41rbp85.pdf

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

[1] We present a georeferenced photomosaic of the Lucky Strike hydrothermal vent field (Mid-Atlantic Ridge, 37°18′N). The photomosaic was generated from digital photographs acquired using the ARGO II seafloor imaging system during the 1996 LUSTRE cruise, which surveyed a ∼1 km2 zone and provided a coverage of ∼20% of the seafloor. The photomosaic has a pixel resolution of 15 mm and encloses the areas with known active hydrothermal venting. The final mosaic is generated after an optimization that includes the automatic detection of the same benthic features across different images (feature-matching), followed by a global alignment of images based on the vehicle navigation. We also provide software to construct mosaics from large sets of images for which georeferencing information exists (location, attitude, and altitude per image), to visualize them, and to extract data. Georeferencing information can be provided by the raw navigation data (collected during the survey) or result from the optimization obtained from image matching. Mosaics based solely on navigation can be readily generated by any user but the optimization and global alignment of the mosaic requires a case-by-case approach for which no universally software is available. The Lucky Strike photomosaics (optimized and navigated-only) are publicly available through the Marine Geoscience Data System (MGDS, http://www.marine-geo.org). The mosaic-generating and viewing software is available through the Computer Vision and Robotics Group Web page at the University of Girona (http://eia.udg.es/∼rafa/mosaicviewer.html).

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2008GC002204

Globally aligned photomosaic of the Lucky Strike hydrothermal vent field (Mid‐Atlantic Ridge, 37°18.5′N): Release of georeferenced data, mosaic construction, and viewing software

Detecting changes between images of the same scene taken at different times is of great interest for monitoring and understanding the environment It is widely used for on-land application but suffers from different constraints Unfortunately, Change detection algorithms require highly accurate geometric and photometric registration This requirement has precluded their use in underwater imagery in the past In this paper, the change detection techniques available nowadays for on-land application were analyzed and a method to automatically detect the changes in sequences of underwater images is proposed Target application scenarios are habitat restoration sites, or area monitoring after sudden impacts from hurricanes or ship groundings The method is based on the creation of a 3D terrain model from one image sequence over an area of interest This model allows for synthesizing textured views that correspond to the same viewpoints of a second image sequence The generated views are photometrically matched and corrected against the corresponding frames from the second sequence Standard change detection techniques are then applied to find areas of difference Additionally, the paper shows that it is possible to detect false positives, resulting from non-rigid objects, by applying the same change detection method to the first sequence exclusively The developed method was able to correctly find the changes between two challenging sequences of images from a coral reef taken one year apart and acquired with two different cameras

/pdf/towards-detecting-changes-in-underwater-image-sequences-1pt8eviim4.pdf

Towards Detecting Changes in Underwater Image Sequences

Over the past decade, image mosaicing has become as an important tool for several different areas such as panoramic photography, mapping, scene stabilization, video indexing and compression. Although recent advances in detection of image correspondences have resulted in very good image registration, global alignment is still needed to obtain a globally coherent mosaic. Normally, global alignment requires the non-linear minimization of an error term, which is defined from image correspondences. In this paper, a new global alignment method is presented. It works on the mosaic frame and does not require any non-linear optimization. The proposed method has been tested with several image sequences and comparative results are presented to illustrate its performance.

O. Delaunoy

Papers

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Globally aligned photomosaic of the Lucky Strike hydrothermal vent field (Mid‐Atlantic Ridge, 37°18.5′N): Release of georeferenced data, mosaic construction, and viewing software

Towards Detecting Changes in Underwater Image Sequences

A New Global Alignment Method for Feature Based Image Mosaicing