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IEEE

OCEANS'15 Washington, DC

Student Poster Competition, OCEANS’15 MTS/IEEE WASHINGTON DC

This 37th Student Poster Program of the OCEANS Conferences was held at OCEANS’15 MTS/IEEE Washington, at the Gaylord National Resort & Convention Center, from October 19 to October 22. The program was organized by Liesl Hotaling (MTS SPC Chair) as local coordinator and Philippe Courmontagne, SPC Chair, from IEEE OES. The program was funded by grants from the Office of Naval Research. For this edition, 104 abstracts were received and 19 were selected for this contest, not without difficulty given the high quality of the received abstracts. Students came from China, Canada, Italy, France and the United States.

     The posters were on display in the Exhibition Hall, allowing the students to exchange and describe their research work to the community. The posters were judged by a team organized by IEEE OES and MTS. The roster of students and their schools are (in order of appearance of the Program Book):

  • Jeffrey Ellen, University of California, San Diego
  • Jonathan Soli, Duke University
  • Antonella Colucci, University of Palermo, Italy
  • Yang Zhang, Ocean University of China & University of Miami
  • Xiao Liu, Dalhousie University
  • Thanh Huy Nguyen, Telecom Bretagne, France
  • Jing Hao, Tsinghua University, China
  • Vittorio Bichucher, University of Michigan
  • Paul Ozog, University of Michigan
  • Minjian Cai, Zhejiang University, China
  • Jie Lie, University of Michigan
  • Eduardo Iscar Ruland, University of Michigan
  • Katherine Skinner, University of Michigan
  • Yishu Shi, Beijing Normal University, China
  • Luke Rumbaugh, Clarkson University
  • Yali Wang, Memorial University of Newfoundland
  • Xiaoxu Cao, Zhejiang University
  • Qingyun Yan, Memorial University of Newfoundland
The commemorative ceremony
The awards ceremony

      The judging was completed by noon on Thursday and the prizes were awarded in the Exhibition Hall. The ceremony began with some few words from Liesl Hotaling, recalling the history of this Student Poster Competition, initiated and championed by Norman Miller, who passed away in July 2015. Next, Ray Toll, MTS President, and René Garello, IEEE OES President, have presented a Student Poster Competition retrospective and a commemorative plaque honoring Norman Miller to Ellen Livingston, University Research Initiatives, Office of Naval Research.
     Then, Philippe Courmontagne called all of the students on stage and presented each student with a certificate for their participation in the program. Ellen Livingstone was called up to present the awards. The third prize was awarded to Jie Li, from the United States, the second prize to Luke Rumbaugh, from the United States and the first prize, the “Norman Miller’s Prize” to Jeffrey Ellen, for his poster entitled “Quantifying California Current Plankton Samples with Efficient Machine Learning Techniques”. The audience gave the students a big hand following the awards presentations. The session ended with a photograph session.
     The roster of students and their poster titles are given below with an abstract of their paper.

 


Jeffrey Ellen, University of California, San Diego
Quantifying California Current Plankton Samples with Efficient Machine Learning Techniques
     This paper improves on the accuracy of other published machine learning results for quantifying plankton samples. The contributions of this work are: (1) Clarifying the number of expertly labeled images required for machine learning results. (2) Providing guidance as to what algorithms provide the best performance, and how to tune them. (3) Leveraging an ensemble of models to achieve recall rates beyond any single algorithm. (4) Investigating the applicability of abstaining. (5) Using size fractionation to learn more efficiently. (6) Analysis of efficacy of simple geometric features for plankton identification.

 

Jonathan Soli, Duke University
     Co-Prime Comb Signals for Active Sonar
     This paper presents an active sonar waveform that achieves range-Doppler performance similar to a uniform frequency comb, but uses far fewer tones to do so. The trade-off for this reduction in occupied bandwidth is a larger bandwidth extent. Co-prime comb signals consist of tones at non-uniformly spaced frequencies according to a 2-level nested co-prime array structure. Specialized non-matched filter processing enables recovery of an ambiguity surface similar to that of a uniform comb, but using fewer tonal components. This reduction in occupied bandwidth offers potential benefits such as sharing, interference avoidance, and Signal-to-Noise Ratio (SNR) improvements in both peak- and total-power-limited scenarios.

 

Antonella Colucci, University of Palermo, Italy
     An inertial system for the production of electricity and hydrogen from seawave energy
     This paper aims at describing a small scale prototype of a complete wave energy converter system for hydrogen production promoting the opportunity of installation in Sicily, in the Mediterranean Sea. The opportunity to produce hydrogen from sea-water identifies ocean wave energy as the most promising solution for electricity generation including hydrogen production and storage. Even if hydrogen is considered one of the most promising secondary sources, criticism arises from both the academic and the industrial world mainly because hydrogen production requires electricity consumption. Furthermore, safety problems concerning hydrogen storage and transport are actually the main hindrance to full commercialization. In order to overcome production issues, hydrogen production and storage plants which are fully powered by renewable sources are continuously investigated. Advantages of the proposed system mainly rely on producing hydrogen by wave energy providing for on-board storage thus avoiding transport-related issues.

Yang Zhang, Ocean University of China & University of Miami
     Seafloor video compression using adaptive hybrid wavelets and directional filter banks
     In this paper, a new video compression technique based on adaptive hybrid wavelets and directional filter banks is proposed to achieve both high coding efficiency and good reconstruction quality at very low-bit rates. A key application is the real-time transmission of video from an autonomous underwater vehicle to a surface station, e.g., for man-in-the-loop monitoring and inspection operations, through acoustic channels that have limited bandwidth. The proposed method can maintain details in texture regions at relatively low bit rates, while overcoming the ringing artifacts within smooth regions, for intra-frame coding. For inter-frame coding, improved efficiency is achieved by making use of: 1) a new spatio-temporal just-noticeable-distortion model to remove perceptual redundancy; 2) motion interpolation to reduce bit rate; 3) variable-precision in quantizing the residual error; and 4) block inter-leaver to reduce transmission errors. Experiments with underwater video sequences are presented to assess the effectiveness of the proposed approach, in comparison to traditional wavelet-based techniques.

Xiao Liu, Dalhousie University
     Acoustic Doppler Compensation using Feedforward Retiming for Underwater Coherent Transmission
     This paper presents a Doppler compensation architecture to maintain a reliable communication link at the receiver in highly mobile applications. It can recover both symbol timing and carrier frequency offset introduced by the Doppler effect. The standard feedback timing recovery loop has been modified into a feedforward architecture to achieve fast timing convergence and power efficiency. The timing error is tracked by a Gardner detector through all samples before decimation. Further, a control unit uses the timing error information to dynamically adjust the sampling time as well as the carrier frequency offset such that the Doppler shift is fully compensated.

Thanh Huy Nguyen, Telecom Bretagne, France
     Correlation bias analysis – A novel method of sinus cardinal model for least squares estimation in cross-correlation
     On the subject of discrete time delay estimation (TDE), especially in the domain of sonar signal processing, in order to determine the time delays between signals received by two separate sensors, TDE techniques involve in locating the peak of cross-correlation function (CCF) between these signals. In many widely used applications of TDE, bias errors of delay estimate can occur when we try to fit the correlation function with a curve that may have an irrelevant shape, for example a parabola or a cosine. This paper thus addresses an analysis of correlation bias in estimating the time delay between a reference signal and a delayed signal by their CCF. Furthermore, we will also introduce a novel bias reduced approach for discrete TDE based on a sinus cardinal model fitting on the CCF of these two sampled signals. The experimental results have shown that the proposed method can provide relevant detection on simulated signals.

Jing Hao, Tsinghua University, China
     Real-time Fish Localization with Binarized Normed Gradients
     Fast and accurate fish localization is an important step for fish detection, identification, counting and tracking. In this paper, we introduce how to localize the fish with an efficient way, which can capture almost all fish locations in an image. First, we exploit the normed gradients (NG) feature of 8×8 image windows to discriminate the fish from the background, and then we binarize the NG feature to accelerate the fish localization. As there is no existing appropriate dataset, we make a dataset of underwater imagery to achieve fish localization. The dataset contains 9,963 images of underwater videos for training, validation and testing. The details about how to label the fish of this dataset further be showed. Last, we evaluate our method on this dataset. Experiments show that our method is fast and efficient, and fish localization takes only about 0.00234 sec. per image (400 fps on an Intel i5-3540 CPU) and achieves 97.1% recall with 1000 proposals. This method satisfies computational efficiency and high detection rate simultaneously.

Vittorio Bichucher, University of Michigan
     Bathymetric Factor Graph SLAM with Sparse Point Cloud Alignment
     This paper reports on a factor graph simultaneous localization and mapping framework for autonomous underwater vehicle localization based on terrain-aided navigation. The method requires no prior bathymetric map and only assumes that the autonomous underwater vehicle has the ability to sparsely sense the local water column depth, such as with a bottom-looking Doppler velocity log. Since dead-reckoned navigation is accurate in short time windows, the vehicle accumulates several water column depth point clouds – or submaps—during the course of its survey. We propose an xy-alignment procedure between these submaps in order to enforce consistent bathymetric structure over time, and therefore attempt to bound long-term navigation drift. We evaluate the submap alignment method in simulation and present performance results from multiple autonomous underwater vehicle field trials.

Paul Ozog, University of Michigan
     Identifying Structural Anomalies in Image Reconstructions of Underwater Ship Hulls
     This paper reports on an algorithm enabling an autonomous underwater vehicle (AUV) to localize into a 3D computer aided design (CAD) model of a ship hull in situ using an optical camera and Doppler velocity log (DVL). The precision of our localization algorithm allows the identification of structural deviations between 3D structure inferred from bundle-adjusted camera imagery and the CAD model. These structural deviations are clustered into shapes, which allow us to fuse camera-derived structure into a CAD-derived 3D mesh. This augmented CAD model can be used within a 3D photomosaicing pipeline, providing a visually intuitive 3D reconstruction of the ship hull. We evaluate our algorithm on the Bluefin Robotics Hovering Autonomous Underwater Vehicle (HAUV) surveying the SS Curtiss, and provide a 3D reconstruction that fuses the CAD mesh with 3D information corresponding to underwater structure, such as biofouling.

Minjian Cai, Zhejiang University, China
     Hydrodynamic Analysis of A Rim-driven Thruster Based on RANS Method
     Rim-driven thruster is gaining wide attention in applications such as underwater vehicles and low-speed vessels. Literature on the influence of rotating rim and the rim-fixed blades on performance is scanty. In this paper, a rim-driven propeller was modeled with its hydrodynamic performance numerically simulated by a commercial Reynolds-averaged Navier-Stokes equation solver. The influence of rim on the wake field and friction loss was studied by simulations using rims of different lengths. The results show a long rim will increase friction torque slightly and will induce a circumferential velocity to the local flow, which means at blade tip region the relative tangential velocity of inflow to the blade section reduces and the pitch angle increases. Analysis of the pressure contours indicates the rim-driven propeller is easier to cause cavitation problem if directly modified from Ka-series. In addition, a following blade thickness study shows the thin blade has an efficiency advantage over the thick one.

Jie Lie, University of Michigan
     Underwater Robot Localization in the Presence of Dramatic Appearance Changes
     This paper reports on an algorithm for underwater visual place recognition in the presence of dramatic appearance change. Long-term visual place recognition is challenging underwater due to biofouling, corrosion, and other effects that lead to dramatic visual appearance change, which often causes traditional point-based feature methods to perform poorly. Building upon the authors’ earlier work, this paper presents an algorithm for underwater vehicle place recognition and relocalization that enables an autonomous underwater vehicle (AUV) to relocalize itself to a previously-built simultaneous localization and mapping (SLAM) graph. High-level structural features are learned using a supervised learning framework that retains features that have a high potential to persist in the underwater environment. Combined with a particle filtering framework, these features are used to provide a probabilistic representation of localization confidence. The algorithm is evaluated on real data, from multiple years, collected by a Hovering Autonomous Underwater Vehicle (HAUV) for ship hull inspection.

Eduardo Iscar Ruland, University of Michigan
     Autonomous Surface Vehicle 3D Seafloor Reconstruction from Monocular Images and Sonar Data
     Traditionally seafloor surveys have been conducted with research vessels, divers or with an autonomous underwater vehicle (AUV) and are time consuming, expensive and high risk. In this paper we present an approach to merge sonar and monocular images to perform large scale mapping of shallow areas from an autonomous surface vessel (ASV), reducing the mission time, cost and risk. Our method uses multibeam sonar data to generate a mesh of the seafloor. Optical images are then blended and projected onto the mesh after a color correction process which increases contrast and overall image quality. In applicable scenarios, ASVs offer an alternative approach to AUVs for autonomous acoustic and optical site mapping. ASVs are typically less expensive than AUVs and often offer easier deployment and recovery logistics. Also, the mechanical requirements are less demanding because they do not have to withstand increased atmospheric water pressure at depth.

Katherine Skinner, University of Michigan
     Detection and Segmentation of Underwater Archaeological Sites Surveyed with Stereo-Vision Platforms
     This paper proposes a method for automating detection and segmentation of archaeological structures in underwater environments. Underwater archaeologists have recently taken advantage of robotic or diver-operated stereo-vision platforms to survey and map submerged archaeological sites. From the acquired stereo images, 3D reconstruction can be performed to produce high-resolution photo-mosaic maps that are metrically accurate and contain information about depth. Archaeologists can then use these maps to manually outline or sketch features of interest, such as building plans of a submerged city. These features often contain large rocks that serve as the foundation to buildings and are arranged in patterns and geometric shapes that are characteristic of human-made structures. Our proposed method first detects these large rocks based on texture and depth information. Next, we exploit the characteristic geometry of human-made structures to identify foundation rocks arranged along lines to form walls. Then we propose to optimize the outlines of these walls by using the gradient of depth to seek the local minimum of the height from the seafloor to identify the ground plane at the base of the rocks. Finally, we output contours as geo-referenced layers for geographic information system (GIS) and architectural planning software. Experiments are based on a 2010 stereo reconstruction survey of Pavlopetri, a submerged city off the coast of Greece. The results provide a proof-of-concept for automating extraction of archaeological structure in underwater environments to produce geo-referenced contours for further analysis by underwater archaeologists.

Yishu Shi, Beijing Normal University, China
     Sparse-Representation-Based Adaptive Interference Suppression
     Passive sources localization in the presence of strong interferences is generally a difficult problem. A sparse-representation-based adaptive interference suppression (SRAIS) method is proposed in this paper for interference suppression and bearing estimation, which can reduce the power loss of the TOI signal and have more accurate direction-of-arrival (DOA) estimation, especially when the input powers of the TOI signal and the interferences are at the almost same level. Simulation and experimental results are also given.

 

 

Luke Rumbaugh, Clarkson University
     A Wideband Noise-like Transmitter Approach for Underwater Lidar using Diode Lasers and Passive Fiber Optic Processor
     A new wideband noise-like transmitter approach is presented for high resolution underwater lidar sensing. The transmitter approach is based on small-footprint, low-cost components, using low coherence time laser diodes and passive fiber processors to generate wideband noise-like intensity modulation signals in the blue-green optical spectrum. Prototype transmitters are demonstrated using both blue and green laser diodes with passive fiber interferometer structures. Laboratory water tank experiments using a two-diode 516/518 nm prototype transmitter show centimeter range error and 30 cm range resolution while detecting a submerged gray target in up to ten attenuation lengths of turbid water. Experimentally observed challenges for target rangefinding are discussed, including shot noise, backscatter returns, and self-clutter. Strategies are proposed to mitigate these challenges and enhance performance when operating at long standoff distances in turbid waters.

Yali Wang, Memorial University of Newfoundland
     Wind direction retrieval from rain-contaminated X-band nautical radar images
     In this paper, an algorithm for retrieving wind direction from rain-contaminated radar images collected under low wind speed conditions is presented. The algorithm investigates radar backscatter in the wavenumber domain and determines wind directions based on spectral components with wavenumbers of [0.01, 0.2]. The algorithm has been tested using rain-contaminated X-band marine radar images and shipborne anemometer data collected on the east coast of Canada. Comparison with the anemometer data shows the root mean square error of wind direction retrieved from rain-contaminated images collected under low wind speeds is reduced by 25.2.

 

Xiaoxu Cao, Zhejiang University
     The adaptive robust tracking control of deep-sea hydraulic manipulator based on backstepping design
     In this paper, design and experiments of the 4500m deep-sea manipulator are introduced. With the extreme working condition, the deep-sea manipulator is more complex and the study is more challenging. The design highlight is stressed, including the double screw pairs elbow joint which could transmit large torque with a compact size, principle of pressure compensator which could balance the water pressure and so on. To achieve high tracking performance, the adaptive robust tracking control based on backstepping algorithm is proposed. The unknown parameters are estimated to enhance the tracking precision. Simulations and experiments based on this algorithm has been performed to verify the controller, the results show that the joint tracking control is fast and smooth, the overshot is small.

Qingyun Yan, Memorial University of Newfoundland
     A Process to Simulate GNSS-R Delay-Doppler Map of Tsunami-dominant Sea Surface
     In this paper, a process is presented to simulate Global Navigation Satellite System-Reflectometry (GNSSR) delay-Doppler maps (DDMs) of a tsunami-dominant sea surface. In this method, the bistatic scattering Z-V model, the sea surface mean square slope model of Cox and Munk and the tsunami-induced wind perturbation model are employed. By taking advantage of the first two models, the DDMs of tsunami-free region can be simulated. In order to accomplish the DDM simulation of tsunami-dominant surface, the tsunami induced wind perturbation model is utilized on top of that. The simulations of the scattering coefficient distribution and the corresponding DDMs of a fixed region of interest before and during the tsunami are exhibited. On the final stage of analysis, by subtracting the simulation results that are free of tsunami from simulations with presence of tsunami, the tsunami-induced variations can be clearly observed. The process is implemented based on the 2004 Sumatra-Andaman tsunami.