Benthic monitoring with robotic platforms — The experience of Australia

Australias Integrated Marine Observing System (IMOS) has a strategic focus on the impact of major boundary currents on continental shelf environments, ecosystems and biodiversity. To improve our understanding of natural, climate change, and human-induced variability in shelf environments, the IMOS Autonomous Underwater Vehicle (AUV) facility has been charged with generating physical and biological observations of benthic variables that cannot be cost-effectively obtained by other means. Starting in 2010, the IMOS AUV facility began collecting precisely navigated benthic imagery using AUVs at selected reference sites on Australias shelf. This observing program capitalizes on the unique capabilities of AUVs that have allowed repeated visits to the reference sites, providing a critical observational link between oceanographic and benthic processes. This paper provides a brief overview of the relevant capabilities of the AUV facility, the design of the IMOS benthic sampling program, and some preliminary results. We also report on some of the challenges and potential benefits to be realized from a benthic observation system that collects several TB of geo-referenced stereo imagery a year. This includes collaborative semi-automated image analysis, clustering and classification, large scale visualization and data mining, and lighting correction for change detection and characterization. We also mention some of the lessons from operating an AUV-based monitoring program and future work in this area.

[1]  Stefan B. Williams,et al.  Colour-Consistent Structure-from-Motion Models using Underwater Imagery , 2012, Robotics: Science and Systems.

[2]  Stefan B. Williams,et al.  Rugosity, slope and aspect from bathymetric stereo image reconstructions , 2010, OCEANS'10 IEEE SYDNEY.

[3]  Stefan B. Williams,et al.  Classification with probabilistic targets , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  C. Roman,et al.  Seabed AUV offers new platform for high‐resolution imaging , 2004 .

[5]  Nicole A. Hill,et al.  Object based segmentation of multibeam backscatter data: methods for spatial analysis of shallow coastal seabeds, South Eastern Tasmania, Australia , 2010 .

[6]  Chris Murphy,et al.  Deep sea underwater robotic exploration in the ice-covered Arctic ocean with AUVs , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Stefan B. Williams,et al.  Plenoptic flow: Closed-form visual odometry for light field cameras , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Stefan B. Williams,et al.  Towards autonomous habitat classification using Gaussian Mixture Models , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Matthew Johnson-Roberson,et al.  Repeatable Robotic Surveying of Marine Benthic Habitats for Monitoring Long-term Change , 2012 .

[10]  Stefan B. Williams,et al.  Water column current aided localisation for significant horizontal trajectories with Autonomous Underwater Vehicles , 2011, OCEANS'11 MTS/IEEE KONA.

[11]  R. García,et al.  Large-Area Photo-Mosaics Using Global Alignment and Navigation Data , 2007, OCEANS 2007.

[12]  Stefan B. Williams,et al.  Simultaneous Localisation and Mapping and Dense Stereoscopic Seafloor Reconstruction Using an AUV , 2008, ISER.

[13]  Stefan B. Williams,et al.  Efficient View-Based SLAM Using Visual Loop Closures , 2008, IEEE Transactions on Robotics.

[14]  P. Hanrahan,et al.  Light Field Photography with a Hand-held Plenoptic Camera , 2005 .

[15]  Stefan B. Williams,et al.  High resolution, consistent navigation and 3D optical reconstructions from AUVs using magnetic compasses and pressure-based depth sensors , 2010, OCEANS'10 IEEE SYDNEY.

[16]  Stefan B. Williams,et al.  A featureless approach to efficient bathymetric SLAM using distributed particle mapping , 2011, J. Field Robotics.

[17]  Hailin Jin,et al.  Light field video stabilization , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[18]  Leonard T. Bruton,et al.  Gradient-based depth estimation from 4D light fields , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[19]  Stefan B. Williams,et al.  Monitoring of Benthic Reference Sites: Using an Autonomous Underwater Vehicle , 2012, IEEE Robotics & Automation Magazine.

[20]  G. Eberli,et al.  Autonomous underwater vehicle (AUV) mapping reveals coral mound distribution, morphology, and oceanography in deep water of the Straits of Florida , 2006 .

[21]  Stefan B. Williams,et al.  Active learning using a Variational Dirichlet Process model for pre-clustering and classification of underwater stereo imagery , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Tom E. Bishop,et al.  The Light Field Camera: Extended Depth of Field, Aliasing, and Superresolution , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Stefan B. Williams,et al.  A Bayesian Nonparametric Approach to Clustering Data from Underwater Robotic Surveys , 2011 .

[24]  Stefan B. Williams,et al.  Autonomous Underwater Vehicle (AUV) for mapping marine biodiversity in coastal and shelf waters: Implications for marine management , 2010, OCEANS'10 IEEE SYDNEY.

[25]  R. Henthorn,et al.  High-Resolution Multibeam and Subbottom Surveys of Submarine Canyons, Deep-Sea Fan Channels, and Gas Seeps Using the MBARI Mapping AUV , 2006, OCEANS 2006.

[26]  G. Kendrick,et al.  Modelling distribution of marine benthos from hydroacoustics and underwater video , 2008 .

[27]  N. Storkersen,et al.  HUGIN-AUV concept and operational experiences to date , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[28]  Hanumant Singh,et al.  Using the Seabed AUV to Assess Populations of Groundfish in Untrawlable Areas , 2009 .

[29]  Stefan B. Williams,et al.  FFT-based Terrain Segmentation for Underwater Mapping , 2012, Robotics: Science and Systems.

[30]  Stefan B. Williams,et al.  Generation and visualization of large‐scale three‐dimensional reconstructions from underwater robotic surveys , 2010, J. Field Robotics.

[31]  Hanumant Singh,et al.  Visually Mapping the RMS Titanic: Conservative Covariance Estimates for SLAM Information Filters , 2006, Int. J. Robotics Res..

[32]  Stefan B. Williams,et al.  Light field image denoising using a linear 4D frequency-hyperfan all-in-focus filter , 2013, Electronic Imaging.

[33]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[34]  Badrinath Roysam,et al.  Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.

[35]  Stefan B. Williams,et al.  Topic-based habitat classification using visual data , 2009, OCEANS 2009-EUROPE.

[36]  Stefan B. Williams,et al.  Water column current profile aided localisation combined with view-based SLAM for Autonomous Underwater Vehicle navigation , 2011, 2011 IEEE International Conference on Robotics and Automation.

[37]  C. Roman,et al.  Imaging Coral I: Imaging Coral Habitats with the SeaBED AUV , 2004 .

[38]  Hanumant Singh,et al.  Toward large-area mosaicing for underwater scientific applications , 2003 .

[39]  Stefan B. Williams,et al.  Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions , 2012, PloS one.

[40]  Stefan B. Williams,et al.  Autonomous underwater vehicle–assisted surveying of drowned reefs on the shelf edge of the Great Barrier Reef, Australia , 2010, J. Field Robotics.

[41]  Stefan B. Williams,et al.  Seabed modeling and distractor extraction for mobile AUVs using light field filtering , 2011, 2011 IEEE International Conference on Robotics and Automation.

[42]  Stefan B. Williams,et al.  AUV Benthic Habitat Mapping in South Eastern Tasmania , 2009, FSR.

[43]  O. Pizarro,et al.  Automated species detection: An experimental approach to kelp detection from sea-oor AUV images , 2012 .

[44]  Stefan B. Williams,et al.  Repeated AUV surveying of urchin barrens in North Eastern Tasmania , 2010, 2010 IEEE International Conference on Robotics and Automation.

[45]  Ren Ng Fourier Slice Photography , 2005 .

[46]  Brian Bingham,et al.  Techniques for Deep Sea Near Bottom Survey Using an Autonomous Underwater Vehicle , 2007, Int. J. Robotics Res..

[47]  Stefan B. Williams,et al.  Bathymetric particle filter SLAM using trajectory maps , 2012, Int. J. Robotics Res..