Ian Mahon

Efficient View-Based SLAM Using Visual Loop Closures

This paper presents a simultaneous localization and mapping algorithm suitable for large-scale visual navigation. The estimation process is based on the viewpoint augmented navigation (VAN) framework using an extended information filter. Cholesky factorization modifications are used to maintain a factor of the VAN information matrix, enabling efficient recovery of state estimates and covariances. The algorithm is demonstrated using data acquired by an autonomous underwater vehicle performing a visual survey of sponge beds. Loop-closure observations produced by a stereo vision system are used to correct the estimated vehicle trajectory produced by dead reckoning sensors.

Simultaneous localisation and mapping on the Great Barrier Reef

This paper presents results of the application of the simultaneous localisation and mapping algorithm to data collected by an unmanned underwater vehicle operating on the Great Barrier Reef in Australia. By fusing information from the vehicles on-board sonar and vision systems, it is possible to use the highly textured reef to provide estimates of the vehicle motion as well as to generate models of the gross structure of the underlying reefs. Terrain-aided navigation promises to revolutionise the ability of marine systems to track underwater bodies in many applications. This work represents a crucial step in the development of underwater technologies capable of long-term, reliable deployment. Results of the application of this technique to the tracking of the vehicle position are shown.

Monitoring of Benthic Reference Sites: Using an Autonomous Underwater Vehicle

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 Australias 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 Australias 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 Australias 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.

Mapping Submerged Archaeological Sites using Stereo‐Vision Photogrammetry

Creating photo-mosaics and plans of submerged archaeological sites quickly, cost-effectively and, most importantly, to a high level of geometric accuracy remains a huge challenge in underwater archaeology. This paper describes a system that takes geo-referenced stereo imagery from a diver-propelled platform and combines it with mapping techniques widely used in the field of robotic science to create high-resolution 2D photo-mosaics and detailed 3D textured models of submerged archaeological features. The system was field tested on the submerged Bronze Age town of Pavlopetri off the coast of Laconia, Greece, in 2010. This paper outlines the equipment used, data collection in the field, image processing and visualization methodology.

Plenoptic flow: Closed-form visual odometry for light field cameras

Three closed-form solutions are proposed for six degree of freedom (6-DOF) visual odometry for light field cameras. The first approach breaks the problem into geometrically driven sub-problems with solutions adaptable to specific applications, while the second generalizes methods from optical flow to yield a more direct approach. The third solution integrates elements into a remarkably simple equation of plenoptic flow which is directly solved to estimate the cameras motion. The proposed methods avoid feature extraction, operating instead on all measured pixels, and are therefore robust to noise. The solutions are closed-form, computationally efficient, and operate in constant time regardless of scene complexity, making them suitable for real-time robotics applications. Results are shown for a simulated underwater survey scenario, and real-world results demonstrate good performance for a three-camera array, outperforming a state-of-the-art stereo feature-tracking approach.

Simultaneous Localisation and Mapping and Dense Stereoscopic Seafloor Reconstruction Using an AUV

This paper reviews current work being undertaken at the University of Sydney’s Australian Centre for Field Robotics on efficient, stereo based Simultaneous Localisation and Mapping and dense scene reconstruction suitable for creating detailed maps of seafloor survey sites. A suite of tools have been developed for creating and visualising accurate models of the seafloor, thereby providing marine scientists with a method for assessing the spatial distribution of organisms on the seafloor. The Autonomous Underwater Vehicle Sirius has been operated on two major cruises in 2007 as part of the establishment of an AUV Facility associated with the Australia’s Integrated Marine Observing System (IMOS). A series of deployments were undertaken in collaboration with scientist from the Australian Institute of Marine Science (AIMS) to assess benthic habitats off the Ningaloo Reef, Western Australia in May. The AUV was also part of a three week research cruise in September aboard the R/V Southern Surveyor documenting drowned shelf edge reefs at multiple sites in four areas along the Great Barrier Reef. Preliminary outcomes of these cruises are described.

SLAM using natural features in an underwater environment

This paper presents techniques developed to apply the simultaneous localisation and mapping (SLAM) algorithm to an unmanned underwater vehicle operating in an unstructured, natural environment. It is shown that information from on-board sonar and vision sensors can be fused to select and track regions of the environment that may be used as features to estimate the vehicles motion. Results including vehicle pose estimates and resulting environment models are shown for data acquired at the Great Barrier Reef in Australia.

Reconstructing pavlopetri: Mapping the world's oldest submerged town using stereo-vision

This paper presents a vision-based underwater mapping system, which is demonstrated in an archaeological survey of the submerged ancient town of Pavlopetri. The snorkeler or diver operated system provides a low cost alternative to the use of an AUV or ROV in shallow waters. The system produces textured three-dimensional models, which contain significantly more information than traditional archaeological survey methods. The photo-realistic maps that are produced allow further archaeological research to be performed, without diving on a site during the restrictive time limitations of permits and field seasons. The hardware and software components of the mapping system and its method of operation are described, and initial results are presented and discussed.

Repeated AUV surveying of urchin barrens in North Eastern Tasmania

This paper describes an approach to achieving high resolution, repeated benthic surveying using an Autonomous Underwater Vehicle (AUV). A stereo based Simultaneous Localisation and Mapping (SLAM) technique is used to estimate the trajectory of the vehicle during multiple overlapping grid based surveys. The vehicle begins each dive on the surface and uses GPS to navigate to a designated start location. Once it reaches the designated location on the surface, the vehicle dives and executes a pre-programmed grid survey, collecting co-registered high resolution stereo images, multibeam sonar and water chemistry data. A suite of navigation instruments are used while the vehicle is underway to estimate its pose relative to the local navigation frame. Following recovery of the vehicle, the SLAM technique is used to refine the estimated vehicle trajectory and to find loop closures both within each survey and between successive missions to co-register the dives. Results are presented from recent deployments of the AUV Sirius at a site in North Eastern Tasmania. The objective of the deployments described in this work were to document the behaviour of barrens-forming sea sea urchins which have recently become resident in the area. The sea urchins can overgraze luxuriant kelp beds that once dominated these areas, leaving only rocky barrens habitat. The high resolution stereo images and resulting three dimensional surface models allow the nocturnal behaviour of the animals, which emerge to feed predominantly at night, to be described. Co-registered images and resulting habitat models collected during the day and at night are being analysed to describe the behaviour of the sea urchins in more detail.

AUV-assisted surveying of relic reef sites

This paper describes the autonomous underwater vehicle (AUV) Sirius and presents its participation in a scientific expedition to survey drowned reefs along the shelf edge of the Great Barrier Reef (GBR) in Queensland, Australia. The primary function of the AUV was to provide geo-referenced, high-resolution optical imagery to facilitate validation of seabed habitat characterisation based on acoustic data. We describe the AUV capabilities and its operation in the context of the cruise objectives to document these relic reef sites. The data processing pipeline involved in generating SLAM-based navigation and large scale 3D visualizations of survey data is briefly described. We also present preliminary results illustrating the type of data products possible with our system and how these complement data gathered by other ship-borne instruments on the cruise.