1,721,116 research outputs found
Information communication technology (ICT) tools for preservation of underwater environment: A vision-based posidonia oceanica monitoring
No full textUnderwater monitoring activities are crucial for the preservation of marine ecosystems. Currently, scuba divers are involved in data collection campaigns that are repetitive, dangerous, and expensive. This article describes the application of Information Communication Technology (ICT) tools to underwater visual data for monitoring purposes. The data refer to a Posidonia oceanica survey mission carried out by a scuba diver using a Smart Dive Scooter equipped with visual acquisition and acoustic localization systems. An acoustic-based strategy for geo-referencing of the optical dataset is reported. It exploits the synchronization be-tween the audio track extracted from a camera and the transponder pings adopted for the acoustic positioning. The positioning measurements are employed within an extended Kalman filter to estimate the diver’s path during the mission. A visual odometry algorithm is implemented within the filter to refine the navigation state estimation of the diver with respect to the acoustic positioning only. Moreover, a smoothing step based on the Rauch-Tung-Striebel smoother is applied to further improve the estimated diver’s positions. Finally, the article reports the results of two different data processing for monitoring applications. The first one is an image mosaicking obtained by concatenating subsequent frames, whereas the second one refers to a qualitative distribution of the Posidonia oceanica over the mission area accomplished through an image segmentation process. The two outcomes are plotted over a satellite image of the surveyed area, showing that the proposed process is an effective tool capable of facilitating divers in their monitoring and inspection activities
Comparison of Monocular and Stereo Vision approaches for Structure Inspection using Autonomous Underwater Vehicles
No full textPeriodical inspections are a fundamental operation to monitor the status of underwater structures and to assess their need for proper maintenance or repair interventions. Autonomous Underwater Vehicles (AUVs) could represent a viable option to carry out underwater inspection tasks, potentially bringing benefits in terms of safety for human operators and quality of the collected data. Aiming at developing a fully autonomous vision-based inspection strategy, this paper proposes a comparative analysis between monocular and stereo vision approaches for estimating the lateral velocity of an AUV and its orientation with respect to a target surface. The proposed analysis is performed by exploiting a dataset of real underwater images, collected during at-sea experiments in which the Zeno AUV was remotely driven to carry out a pier inspection. Specifically, the performance of the two solutions in terms of estimation of the robot lateral velocity is assessed by considering doppler velocity log measurements as benchmark. Instead, the accuracy of the estimation of the vehicle orientation with respect to the target is evaluated by taking into account both geographical information of the pier and AUV attitude observations. The comparison suggests that stereo vision provides better performance for estimating the relative orientation between the AUV and the target; on the contrary, the monocular approach produces more reliable lateral velocity estimates. The results obtained prove the suitability of the two vision-based strategies for inspection applications in a real underwater scenario, thus suggesting a possible implementation onboard the reference vehicle
Visual-based Navigation Strategy for Autonomous Underwater Vehicles in Monitoring Scenarios
No full textAutonomous Underwater Vehicles (AUVs) performing visual surveys aimed at the preservation of marine environments are equipped with optical sensors for image acquisition. In addition, an altitude sensor is usually installed on-board to control the distance from the seabed and avoid possible collisions. Within this context, this work proposes a navigation strategy for underwater monitoring scenarios, which fuses a single bottom-looking camera and altitude information for linear velocity estimation. This allows to exploit the payload already required by monitoring activities also for navigation purposes, thus reducing the number of sensors onboard the AUV. The linear velocity is provided by a monocular Visual Odometry (VO) technique that switches between homography and epipolar models for motion estimation and leverages altitude measurements to overcome the scale ambiguity issue. The navigation framework relies on an Extended Kalman Filter (EKF) that combines visual-based linear velocity with attitude and depth measurements for trajectory estimation. The proposed strategy has been tested on real data acquired by using Zeno AUV, equipped with bottom-looking camera, DVL, Attitude and Heading Reference System (AHRS), and depth sensor. The performance has been assessed comparing the estimated linear velocities with the DVL readings, and the VO-based estimated trajectory with that provided by a DVL-based dead-reckoning approach, yielding to a maximum absolute error of 2.16m for a reference trajectory of 166m. Given the promising results, this strategy could represent an affordable solution for underwater navigation where visibility conditions allow the use of optical sensors
Stereo Vision System for Autonomous Ship Hull Inspection
No full textThe periodical hull inspection represents a necessary task to ensure the maintenance of a vessel since it allows to counteract decay, check for structural damages, and fight the biofouling phenomenon affecting the navigation efficiency. Typically, this task is executed by divers, resulting in a dangerous job for the human operator, or by Remotely Operated Vehicles, driven by highly trained users. Aiming at automating the task and increasing its operational safety, this work proposes a strategy to perform the ship hull inspection using an Autonomous Underwater Vehicle (AUV), equipped with a stereo camera and a proximity sensor, without a prior knowledge of the target shape. At first, the images from the stereo vision system allow to estimate the lateral velocity of the vehicle and its orientation with respect to the hull surface. Then, the proximity measurement, properly projected along the normal axis to the surface of the target, provides a measure of the distance of the AUV from the surveyed structure. Lastly, the robot control system exploits these estimates to perform the mission with a constant lateral velocity, maintaining both a predefined safety distance from the target and the optical axis of the camera orthogonal to the examined surface. The proposed approach has been tested in a simulated environment, performing the investigation of a simplified model of ship hull. The results suggest the feasibility of the strategy: during the simulations, the AUV completes the mission with a full autonomy, safely, obtaining a 3D reconstruction of the surveyed structure
Autonomous boundary inspection of Posidonia oceanica meadows using an underwater robot
Get PDFMonitoring provides important information for the planning and execution of marine environment preservation operations. Posidonia oceanica is one of the principal bioindicators in Mediterranean coastal areas and regular monitoring activities play a crucial role in its conservation. However, an efficient observation of vast areas colonised with P. oceanica is extremely challenging and it currently requires tedious and time consuming diving activities. Autonomous Underwater Vehicles (AUVs) endowed with optical sensors could represent a viable solution in carrying out visual inspection surveys. Nevertheless, AUVs are usually programmed to perform pre-defined trajectories, which are not effective for seagrass monitoring applications, as meadows may be fragmented and their contours may be irregular. This work proposes a framework based on machine learning and computer vision that enables an AUV equipped with a down-looking camera to autonomously inspect the boundary of P. oceanica meadows to obtain an initial estimate of the meadow size. The proposed boundary inspection solution is composed of three main modules: (1) an image segmentation relying on a Mask R-CNN model to recognise P. oceanica in underwater images, (2) a boundary tracking strategy that generates guidance references to track P. oceanica contours, (3) a loop closure detector fusing visual and navigation information to identify when a meadow boundary has been completely explored. The image segmentation model and the visual part of the loop closure detection module were validated on real underwater images. The overall inspection framework was tested in a realistic simulation environment, using mosaics obtained from real images to replicate the actual monitoring scenarios. The results show that the proposed solution enables the AUV to autonomously accomplish the boundary inspection task of P. oceanica meadows, therefore representing an effective tool towards the conservation and protection of marine environments
Dealing with Feature Correspondence in Visual Odometry for Underwater Applications
No full textThis paper proposes an evaluation of the impact of the 2D feature correspondence stage on an underwater vision-based navigation solution using a monocular Visual Odometry (VO) algorithm for linear velocity estimation. In particular, this work compares three different mismatch removal methods: the Cross-Check (CC), the Lowe's Ratio Test (RT), and the Grid-based Motion Statistics (GMS). The performance of the three methods was assessed using two datasets containing real underwater images, which were collected by an Autonomous Underwater Vehicle (AUV) during monitoring activities over two distinct marine areas exhibiting different seafloor characteristics. The comparison is conducted considering both quantity and quality of features returned by the three approaches. In addition, the influence they have on the overall VO algorithm in terms of linear velocity accuracy is taken into account, using doppler velocity log readings as a reference. The results show that the three techniques are comparable in the case of a seabed characterised by identifiable and discernible features. In contrast, when surveying a more challenging and variable scenario, the RT technique shows a greater ability than CC and GMS to filter out erroneous 2D correspondences. This ensures higher accuracy in estimating the AUV linear velocity by the monocular VO algorithm. Furthermore, in both scenarios analysed, the RT technique is also the one that leads to a lower computational cost of the entire VO algorithm, and thus a better suitability for a real-time application onboard the AUV
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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