394 research outputs found

    Hyperspectral benthic mapping from underwater robotic platforms

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    We live on a planet of vast oceans; 70% of the Earth's surface is covered in water. They are integral to supporting life, providing 99% of the inhabitable space on Earth. Our oceans and the habitats within them are under threat due to a variety of factors. To understand the impacts and possible solutions, the monitoring of marine habitats is critically important. Optical imaging as a method for monitoring can provide a vast array of information however imaging through water is complex. To compensate for the selective attenuation of light in water, this thesis presents a novel light propagation model and illustrates how it can improve optical imaging performance. An in-situ hyperspectral system is designed which comprised of two upward looking spectrometers at different positions in the water column. The downwelling light in the water column is continuously sampled by the system which allows for the generation of a dynamic water model. In addition to the two upward looking spectrometers the in-situ system contains an imaging module which can be used for imaging of the seafloor. It consists of a hyperspectral sensor and a trichromatic stereo camera. New calibration methods are presented for the spatial and spectral co-registration of the two optical sensors. The water model is used to create image data which is invariant to the changing optical properties of the water and changing environmental conditions. In this thesis the in-situ optical system is mounted onboard an Autonomous Underwater Vehicle. Data from the imaging module is also used to classify seafloor materials. The classified seafloor patches are integrated into a high resolution 3D benthic map of the surveyed site. Given the limited imaging resolution of the hyperspectral sensor used in this work, a new method is also presented that uses information from the co-registered colour images to inform a new spectral unmixing method to resolve subpixel materials

    A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

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    The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

    Quantitative Comparison of Benthic Habitat Maps Derived From Multibeam Echosounder Backscatter Data

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    In the last decade, following the growing concern for the conservation of marine ecosystems, a wide range of approaches has been developed to achieve the identification, classification and mapping of seabed types and of benthic habitats. These approaches, commonly grouped under the denominations of Benthic Habitat Mapping or Acoustic Seabed Classification, exploit the latest scientific and engineering advancements for the exploration of the bottom of the ocean, particularly in underwater acoustics. Among all acoustic seabed-mapping systems available for this purpose, a growing interest has recently developed for Multibeam Echosounders (MBES). This interest is mainly the result of the multiplicity of these systems’ outputs (that is, bathymetry, backscatter mosaic, angular response and water-column data), which allows for multiple approaches to seabed or habitat classification and mapping. While this diversity of mapping approaches and this multiplicity of MBES data products contribute to an increasing quality of the charting of the marine environment, they also unfortunately delay the future standardization of mapping methods, which is required for their effective integration in marine environment management strategies. As a preliminary step towards such standardization, there is a need for generalized efforts of comparison of systems, data products, and mapping approaches, in order to assess the most effective ones given mapping objectives and environment conditions. The main goal of this thesis is to contribute to this effort through the development and implementation of tools and methods for the comparison of categorical seabed or habitat maps, with a specific focus on maps obtained from up-to-date methodologies of classification of MBES backscatter data. This goal is attained through the achievement of specific objectives treated sequentially. First, the need for comparison is justified through a review of the diversity characterizing the fields of Benthic Habitat Mapping and Acoustic Seabed Classification, and of their use of MBES data products. Then, a case study is presented that compare the data products from a Kongsberg EM3000 MBES to the output map of an Acoustic Ground Discrimination Software based on data from a Single-beam Echosounder and to a Sidescan Sonar mosaic, in order to illustrate how map comparison measures could contribute to the comparison of these systems. Next, a number of measures for map-to-map comparison, inspired from the literature in land remote sensing, are presented, along with methodologies for their implementation in comparison of maps described with different legends. The benefit of these measures and methodologies is demonstrated through their application to maps obtained from the acoustic datasets presented previously. Finally, a more typical implementation of these measures is presented as a case study in which the development of two up-to-date classification methodologies of MBES backscatter data is complemented by the quantitative comparison of their output maps. In the process of developing and illustrating the use of methods for the assessment of map-to-map similarity, this thesis also presents methodologies for the processing and classification of backscatter data from MBES. In particular, the potential of the combined use of the spatial and angular information of these data for seabed classification is explored through the development of an original segmentation methodology that sequentially divides and aggregates segments defined from a MBES backscatter mosaic on the basis of their angular response content

    Autonomous navigation for guide following in crowded indoor environments

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    The requirements for assisted living are rapidly changing as the number of elderly patients over the age of 60 continues to increase. This rise places a high level of stress on nurse practitioners who must care for more patients than they are capable. As this trend is expected to continue, new technology will be required to help care for patients. Mobile robots present an opportunity to help alleviate the stress on nurse practitioners by monitoring and performing remedial tasks for elderly patients. In order to produce mobile robots with the ability to perform these tasks, however, many challenges must be overcome. The hospital environment requires a high level of safety to prevent patient injury. Any facility that uses mobile robots, therefore, must be able to ensure that no harm will come to patients whilst in a care environment. This requires the robot to build a high level of understanding about the environment and the people with close proximity to the robot. Hitherto, most mobile robots have used vision-based sensors or 2D laser range finders. 3D time-of-flight sensors have recently been introduced and provide dense 3D point clouds of the environment at real-time frame rates. This provides mobile robots with previously unavailable dense information in real-time. I investigate the use of time-of-flight cameras for mobile robot navigation in crowded environments in this thesis. A unified framework to allow the robot to follow a guide through an indoor environment safely and efficiently is presented. Each component of the framework is analyzed in detail, with real-world scenarios illustrating its practical use. Time-of-flight cameras are relatively new sensors and, therefore, have inherent problems that must be overcome to receive consistent and accurate data. I propose a novel and practical probabilistic framework to overcome many of the inherent problems in this thesis. The framework fuses multiple depth maps with color information forming a reliable and consistent view of the world. In order for the robot to interact with the environment, contextual information is required. To this end, I propose a region-growing segmentation algorithm to group points based on surface characteristics, surface normal and surface curvature. The segmentation process creates a distinct set of surfaces, however, only a limited amount of contextual information is available to allow for interaction. Therefore, a novel classifier is proposed using spherical harmonics to differentiate people from all other objects. The added ability to identify people allows the robot to find potential candidates to follow. However, for safe navigation, the robot must continuously track all visible objects to obtain positional and velocity information. A multi-object tracking system is investigated to track visible objects reliably using multiple cues, shape and color. The tracking system allows the robot to react to the dynamic nature of people by building an estimate of the motion flow. This flow provides the robot with the necessary information to determine where and at what speeds it is safe to drive. In addition, a novel search strategy is proposed to allow the robot to recover a guide who has left the field-of-view. To achieve this, a search map is constructed with areas of the environment ranked according to how likely they are to reveal the guide’s true location. Then, the robot can approach the most likely search area to recover the guide. Finally, all components presented are joined to follow a guide through an indoor environment. The results achieved demonstrate the efficacy of the proposed components

    Comparison of a self-processed EM3000 multibeam echosounder dataset with a QTC view habitat mapping and a sidescan sonar imagery, Tamaki Strait, New Zealand

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    A methodology for automatically processing the data files from an EM3000 multibeam echosounder (Kongsberg Maritime, 300 kHz) is presented. Written in MatLab, it includes data extraction, bathymetry processing, computation of seafloor local slope, and a simple correction of the backscatter along-track banding effect. The success of the latter is dependent on operational restrictions, which are also detailed. This processing is applied to a dataset acquired in 2007 in the Tamaki Strait, New Zealand. The resulting maps are compared with a habitat classification obtained with the acoustic ground-discrimination software QTC View linked to a 200-kHz single-beam echosounder and to the imagery from a 100-kHz sidescan sonar survey, both performed in 2002. The multibeam backscatter map was found to be very similar to the sidescan imagery, quite correlated to the QTC View map on one site but mainly uncorrelated on another site. Hypotheses to explain these results are formulated and discussed. The maps and the comparison to prior surveys are used to draw conclusions on the quality of the code for further research on multibeam benthic habitat mapping

    NASA Tech Briefs, May 2011

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    Topics covered include: 1) Method to Estimate the Dissolved Air Content in Hydraulic Fluid; 2) Method for Measuring Collimator-Pointing Sensitivity to Temperature Changes; 3) High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence; 4)Metrology Arrangement for Measuring the Positions of Mirrors of a Submillimeter Telescope; 5) On-Wafer S-Parameter Measurements in the 325-508-GHz Band; 6) Reconfigurable Microwave Phase Delay Element for Frequency Reference and Phase-Shifter Applications; 7) High-Speed Isolation Board for Flight Hardware Testing; 8) High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors; 9) 3D Orbit Visualization for Earth-Observing Missions; 10) MaROS: Web Visualization of Mars Orbiting and Landed Assets; 11) RAPID: Collaborative Commanding and Monitoring of Lunar Assets; 12) Image Segmentation, Registration, Compression, and Matching; 13) Image Calibration; 14) Rapid ISS Power Availability Simulator; 15) A Method of Strengthening Composite/Metal Joints; 16) Pre-Finishing of SiC for Optical Applications; 17) Optimization of Indium Bump Morphology for Improved Flip Chip Devices; 18) Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures; 19) Marshall Convergent Spray Formulation Improvement for High Temperatures; 20) Real-Time Deposition Monitor for Ultrathin Conductive Films; 21) Optimized Li-Ion Electrolytes Containing Triphenyl Phosphate as a Flame-Retardant Additive; 22) Radiation-Resistant Hybrid Lotus Effect for Achieving Photoelectrocatalytic Self-Cleaning Anticontamination Coatings; 23) Improved, Low-Stress Economical Submerged Pipeline; 24) Optical Fiber Array Assemblies for Space Flight on the Lunar Reconnaissance Orbiter; 25) Local Leak Detection and Health Monitoring of Pressurized Tanks; 26) Dielectric Covered Planar Antennas at Submillimeter Wavelengths for Terahertz Imaging; 27) Automated Cryocooler Monitor and Control System; 28) Broadband Achromatic Phase Shifter for a Nulling Interferometer; 29) Super Dwarf Wheat for Growth in Confined Spaces; 30) Fine Guidance Sensing for Coronagraphic Observatories; 31) Single-Antenna Temperature- and Humidity-Sounding Microwave Receiver; 32) Multi-Wavelength, Multi-Beam, and Polarization-Sensitive Laser Transmitter for Surface Mapping; 33) Optical Communications Link to Airborne Transceiver; 34) Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings; 35) Entanglement in Self-Supervised Dynamics; 36) Prioritized LT Codes; 37) Fast Image Texture Classification Using Decision Trees; 38) Constraint Embedding Technique for Multibody System Dynamics; 39) Improved Systematic Pointing Error Model for the DSN Antennas; 40) Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks; 41) More-Accurate Model of Flows in Rocket Injectors; 42) In-Orbit Instrument-Pointing Calibration Using the Moon as a Target; 43) Reliability of Ceramic Column Grid Array Interconnect Packages Under Extreme Temperatures; 44) Six Degrees-of-Freedom Ascent Control for Small-Body Touch and Go; and 45) Optical-Path-Difference Linear Mechanism for the Panchromatic Fourier Transform Spectrometer

    Advances in Sonar Technology

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    The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here

    3-D Coastal Bathymetry Simulation from Airborne TOPSAR Polarized Data

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    Acoustic data optimisation for seabed mapping with visual and computational data mining

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    Oceans cover 70% of Earth’s surface but little is known about their waters. While the echosounders, often used for exploration of our oceans, have developed at a tremendous rate since the WWII, the methods used to analyse and interpret the data still remain the same. These methods are inefficient, time consuming, and often costly in dealing with the large data that modern echosounders produce. This PhD project will examine the complexity of the de facto seabed mapping technique by exploring and analysing acoustic data with a combination of data mining and visual analytic methods. First we test the redundancy issues in multibeam echosounder (MBES) data by using the component plane visualisation of a Self Organising Map (SOM). A total of 16 visual groups were identified among the 132 statistical data descriptors. The optimised MBES dataset had 35 attributes from 16 visual groups and represented a 73% reduction in data dimensionality. A combined Principal Component Analysis (PCA) + k-means was used to cluster both the datasets. The cluster results were visually compared as well as internally validated using four different internal validation methods. Next we tested two novel approaches in singlebeam echosounder (SBES) data processing and clustering – using visual exploration for outlier detection and direct clustering of time series echo returns. Visual exploration identified further outliers the automatic procedure was not able to find. The SBES data were then clustered directly. The internal validation indices suggested the optimal number of clusters to be three. This is consistent with the assumption that the SBES time series represented the subsurface classes of the seabed. Next the SBES data were joined with the corresponding MBES data based on identification of the closest locations between MBES and SBES. Two algorithms, PCA + k-means and fuzzy c-means were tested and results visualised. From visual comparison, the cluster boundary appeared to have better definitions when compared to the clustered MBES data only. The results seem to indicate that adding SBES did in fact improve the boundary definitions. Next the cluster results from the analysis chapters were validated against ground truth data using a confusion matrix and kappa coefficients. For MBES, the classes derived from optimised data yielded better accuracy compared to that of the original data. For SBES, direct clustering was able to provide a relatively reliable overview of the underlying classes in survey area. The combined MBES + SBES data provided by far the best accuracy for mapping with almost a 10% increase in overall accuracy compared to that of the original MBES data. The results proved to be promising in optimising the acoustic data and improving the quality of seabed mapping. Furthermore, these approaches have the potential of significant time and cost saving in the seabed mapping process. Finally some future directions are recommended for the findings of this research project with the consideration that this could contribute to further development of seabed mapping problems at mapping agencies worldwide

    Experiments on Surface Reconstruction for Partially Submerged Marine Structures

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    Over the past 10 years, significant scientific effort has been dedicated to the problem of three-dimensional (3-D) surface reconstruction for structural systems. However, the critical area of marine structures remains insufficiently studied. The research presented here focuses on the problem of 3-D surface reconstruction in the marine environment. This paper summarizes our hardware, software, and experimental contributions on surface reconstruction over the past few years (2008–2011). We propose the use of off-the-shelf sensors and a robotic platform to scan marine structures both above and below the waterline, and we develop a method and software system that uses the Ball Pivoting Algorithm (BPA) and the Poisson reconstruction algorithm to reconstruct 3-D surface models of marine structures from the scanned data. We have tested our hardware and software systems extensively in Singapore waters, including operating in rough waters, where water currents are around 1–2 m/s. We present results on construction of various 3-D models of marine structures, including slowly moving structures such as floating platforms, moving boats, and stationary jetties. Furthermore, the proposed surface reconstruction algorithm makes no use of any navigation sensor such as GPS, a Doppler velocity log, or an inertial navigation system.Singapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Modelin
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