Alberto Ortiz

University of the Balearic Islands, Palma, Balearic Islands, Spain

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Publications (54)15.71 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: Seagoing vessels have to undergo regular inspections, which are currently performed manually by ship surveyors. The main cost factor in a ship inspection is to provide access to the different areas of the ship, since the surveyor has to be close to the inspected parts, usually within arm's reach, either to perform a visual analysis or to take thickness measurements. The access to the structural elements in cargo holds, e.g., bulkheads, is normally provided by staging or by “cherry-picking” cranes. To make ship inspections safer and more cost-efficient, we have introduced new inspection methods, tools, and systems, which have been evaluated in field trials, particularly focusing on cargo holds. More precisely, two magnetic climbing robots and a micro-aerial vehicle, which are able to assist the surveyor during the inspection, are introduced. Since localization of inspection data is mandatory for the surveyor, we also introduce an external localization system that has been verified in field trials, using a climbing inspection robot. Furthermore, the inspection data collected by the robotic systems are organized and handled by a spatial content management system that enables us to compare the inspection data of one survey with those from another, as well as to document the ship inspection when the robot team is used. Image-based defect detection is addressed by proposing an integrated solution for detecting corrosion and cracks. The systems' performance is reported, as well as conclusions on their usability, all in accordance with the output of field trials performed onboard two different vessels under real inspection conditions.
    Journal of Field Robotics 01/2014; · 2.15 Impact Factor
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    ABSTRACT: Vessel maintenance entails periodic visual inspections of the internal and external parts of the hull in order to detect the typical defective situations affecting metallic structures, such as coating breakdown, corrosion, cracks, etc. The main goal of project MINOAS is the automation of the inspection process, currently undertaken by human surveyors, by means of a fleet of robotic agents. This paper overviews an approach to the inspection problem based on an autonomous Micro Aerial Vehicle (MAV) which, as part of this fleet, is in charge of regularly supplying images that can teleport the surveyor from a base station to the areas of the hull to be inspected. The control software approach adopted for the MAV is fully described, with a special emphasis on the self-localization capabilities of the vehicle. Experimental results showing the suitability of the platform to the application are as well reported and discussed.
    Journal of Intelligent and Robotic Systems 01/2014; · 0.83 Impact Factor
  • Francisco Bonnin-Pascual, Alberto Ortiz
    01/2014; , ISBN: 980-953-307-1100-2
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    ABSTRACT: This paper presents a novel approach to perform obstacle avoidance and robot localization using a single camera. This approach is based on the continuous detection and tracking of image features. Features are classified as ground points or obstacle points using the IPT (Inverse Perspective Transformation). Obstacle avoidance is achieved by means of a qualitative local occupancy grid built using the visually detected obstacle points, while the features classified as ground points are used to perform robocentric localization. The experiments, conducted indoors and outdoors, illustrate the range of scenarios where our proposal can be used, and show, both qualitatively and quantitatively, the benefits it provides.
    11/2013;
  • Robotica 01/2013; · 0.88 Impact Factor
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    ABSTRACT: This paper presents an approach to visual obstacle avoidance and reactive robot navigation for outdoor and indoor environments. The obstacle detection algorithm includes an image feature tracking procedure followed by a feature classification process based on the IPT (Inverse Perspective Transformation). The classifier discriminates obstacle points from ground points. Obstacle features permit to draw out the obstacle boundaries which are used to construct a local and qualitative polar occupancy grid, analogously to a visual sonar. The navigation task is completed with a robocentric localization algorithm to compute the robot pose by means of an EKF (Extended Kalman Filter). The filter integrates the world coordinates of the ground points and the robot position in its state vector. The visual pose estimation process is intended to correct possible drifts on the dead-reckoning data provided by the proprioceptive robot sensors. The experiments, conducted indoors and outdoors, illustrate the range of scenarios where our proposal has proved to be useful, and show, both qualitatively and quantitatively, the benefits it provides.
    Robotica 05/2012; · 0.88 Impact Factor
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    ABSTRACT: Starting in January 2009, the RAUVI (Reconfigurable Autonomous Underwater Vehicle for Intervention Missions) project is a 3-year coordinated research action funded by the Spanish Ministry of Research and Innovation. In this paper, the state of progress after 2years of continuous research is reported. As a first experimental validation of the complete system, a search and recovery problem is addressed, consisting of finding and recovering a flight data recorder placed at an unknown position at the bottom of a water tank. An overview of the techniques used to successfully solve the problem in an autonomous way is provided. The obtained results are very promising and are the first step toward the final test in shallow water at the end of 2011. KeywordsUnderwater robotics–Intervention AUV–Autonomous underwater manipulation–Underwater computer vision–Graphical user interfaces
    Intelligent Service Robotics 01/2012; 5(1):19-31.
  • Electronics Letters 01/2012; 48(5):264-266. · 1.04 Impact Factor
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    ABSTRACT: A low-cost, simple and efficient approach to reactive visual navigation addressed to mobile robots, complemented with an accurate localisation algorithm' is presented. The system is mainly supported on the continuous detection and tracking of image features which are classified as obstacle or ground points using the inverse perspective transformation. While obstacle points are used for collision avoidance, ground points are used for localisation in a Rao-Blackwellised particle filter context. Results obtained from experiments conducted indoors and outdoors illustrate the wide range of scenarios where the technique can be successfully employed.
    Electronics Letters 01/2012; 48(5):264-266. · 1.04 Impact Factor
  • Francisco Bonnin-Pascual, Alberto Ortiz
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    ABSTRACT: Vessel maintenance entails periodic visual inspec- tions of internal and external parts of the vessel hull in order to detect structural failures. Typically, this is done by trained surveyors at great cost. Clearly, assisting them during the inspection process by means of a fleet of robots capable of defect detection would decrease the inspection cost. In this paper, a novel algorithm for visual detection of coating breakdown is presented. The algorithm is based on an AdaBoost scheme to combine multiple weak classifiers based on Laws' texture energy filter responses. After a number of enhancements, the method has proved successful, while the execution times remain contained. Index Terms—Coating breakdown detection, Adaptive Boost- ing, Laws' texture energy filters, Classification, Vessel inspec- tion. I. INTRODUCTION Vessels and ships are nowadays one of the most cost effective ways to transport goods around the world. Despite the efforts to avoid maritime accidents and wreckages, these still occur, and, from time to time, have catastrophic con- sequences in environmental, human and/or economic terms. Since structural failures, like coating breakdown, corrosion or cracks are the main cause of these accidents, Classification Societies impose extensive inspection schemes in order to ensure the structural integrity of vessels. An important part of the vessel maintenance has to do with the visual inspection of the internal and external parts oh the hull. To carry out this task, the vessel has to be emptied and situated in a dockyard where high scaffoldings are installed to allow the human inspectors to access the highest parts of the vessel structure (more than 30 m high). Taking into account the huge dimensions of some vessels, this process can mean the visual assessment of more than 600,000 m 2 of steel. Besides, the surveys are on many occasions performed in hazardous environments for which the access is usually difficult and the operational conditions turn out to be sometimes extreme for human operation. Moreover, total expenses involved by the infrastructure needed for close-up inspection of the hull can reach up to one million dollars for certain sorts of vessels (e.g. Ultra Large Crude Carriers, ULCC). Therefore, it is clear that any level of automation of the inspection process that can lead to a reduction of the inspection time, a reduction of the financial costs involved and/or an increase in the safety of the operation is fully justified.
    19th Mediterranean Conference on Control and Automation (MED), Corfu (Greece); 07/2011
  • Alberto Ortiz, Javier Antich, Gabriel Oliver
    Machine Vision and Applications 01/2011; 22:283-302. · 1.10 Impact Factor
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    ABSTRACT: The paper proposes a method that uses topological information to guide the path search in any 2D workspace. As a first contribution, we have extended the method proposed by Jenkins to generate the topological information by taking into consideration the constraints of the workspace during the construction of the topological environment, which is then used to compute topological paths. As a second contribution, a planner based on the Rapidly-exploring Random Tree (RRT), called Homotopic RRT (HRRT) is proposed to use the topological information to guide the path search in the workspace. Finally, simulated and real results with an Autonomous Underwater Vehicle (AUV) are presented showing the feasibility of the proposal. Comparison with well-known path planning algorithms has also been included.
    IEEE International Conference on Robotics and Automation, ICRA 2011, Shanghai, China, 9-13 May 2011; 01/2011
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    ABSTRACT: Starting in January 2009, the RAUVI project is a three years coordinated research action funded by the Spanish Ministry of Research and Innovation. This paper shows the research evolution during the first half of RAUVI's live, bearing in mind that the long term objective is to design and develop an underwater autonomous robot able to perceive the environment and, by means of a specific hand-arm system, perform autonomously simple intervention tasks in shallow waters.
    ELMAR, 2010 PROCEEDINGS; 10/2010
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    ABSTRACT: This paper proposes a mobile robot localization approach based on a monocular vision system. The proposal operates in three main steps. First, image features are extracted from frames gathered at different positions. Second, the obtained features are classified as obstacles or ground points. Third, under the assumption of a flat floor, the ground point coordinates are computed and used to perform localization. The experimental results, performed both in simulation and real environments, validate the proposal.
    Emerging Technologies and Factory Automation (ETFA), 2010 IEEE Conference on; 10/2010
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    ABSTRACT: Reactive visual-based navigation solutions that build or use local occupancy maps representing the area that surrounds the robot and visual sonar-based solutions are sensitive to floor and obstacle textures, homogeneity in the color intensity distribution, edges or lighting conditions. The construction of local maps is a suitable way to clearly identify the presence and position of obstacles and thus to determine the direction to follow. But it is not essential to determine or to identify exact obstacle shapes, dimensions, colors or textures. In this chapter, a new navigation strategy including obstacle detection and avoidance has been presented. The algorithm shows a certain robustness to the presence of shadows, inter-reflections, specularities or textured floors, overcomes scenes with multiple planes and uses only a certain number of image points. The complete strategy starts with a novel image feature classifier that distinguishes with a success rate greater that 90% between obstacle features from features lying on the ground. The detection of points that belong to obstacles permits: a) discriminating the obstacle boundaries from the rest of edges, and b) the detection of obstacle-to-ground contact points. By computing the world coordinates of those obstacle-to-ground contact points detected in the image, the system builds a radial qualitative model of the robot vicinity. Range and angle information are quantitatively and accurately computed to create a qualitative occupancy map. Navigation decisions are taken next on the basis of qualitative criteria. What is reflected in these maps is not the total area that the obstacle occupies or its exact shape or identification, but it is an evidence of the presence of something that has to be avoided in a determined direction and at a defined distance. The experimental setup consisted of different scenarios with different characteristics, different obstacles, different illumination conditions and different floor textures. In all cases the mobile robot was able to navigate through the free space avoiding all obstacles, walls and columns.
    03/2010; , ISBN: 978-953-307-077-3
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    Alberto Ortiz, Gabriel Oliver
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    ABSTRACT: The Dichromatic Reflection Model (DRM) introduced by Shafer in 1985 is surely the most referenced physics-based model of image formation. A preliminary analysis of this model derives in the conclusion that colour channels remain coupled by the reflectance of objects surface material. Taking this observation as a basis, this paper shows that this coupling manifests itself at the signal level in the form of a set of properties only satisfied in uniform reflectance areas. Such properties are deeply analysed and formalized throughout the paper, and, eventually, they are stated geometrically. As will be seen, a compatibility relationship stems from this geometric interpretation, which allows checking at a very low cost whether two pixels correspond to the same scene reflectance or not. Finally, an edge detector based on the use of the previous relationship is presented as an example of application. This edge detector inherits all the properties of the compatibility relationship: simplicity, low computational power requirements, sensor noise adaptivity and insensitivity to image intensity changes due to scene objects curvature.
    Pattern Recognition 01/2010; 43(7):2507-2520. · 2.63 Impact Factor
  • Artificial Intelligence Research and Development - Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence, l'Espluga de Francolí, Tarragona, Spain, 20-22 October 2010; 01/2010
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    F. Bonin-Font, A. Ortiz
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    ABSTRACT: Reactive navigation strategies for mobile robots base their success on the ability to discriminate obstacles from the ground in the vicinity of the robot and many of these strategies are based uniquely on the computation of quantitative information. In this paper we describe a new method to build qualitative local occupancy grids that are used in a new vision-based navigation strategy addressed to mobile robots to explore safely unknown environments. The process includes a new feature classifier based on the inverse perspective transformation to discriminate object from ground points and a method to determine angle and range with respect to the camera in the world coordinate system.
    Emerging Technologies & Factory Automation, 2009. ETFA 2009. IEEE Conference on; 10/2009
  • J. Antich, A. Ortiz, J. Minguez
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    ABSTRACT: In recent years, anytime algorithms have shown to be a good solution for planning a path in domains with severe restrictions regarding the time for deliberation. They typically operate by quickly finding a highly suboptimal path first, and then improving it until the available time runs out. In this paper, we propose a novel anytime approach called ABUG that performs much more efficiently than the competing strategies. ABUG is based on an improved version of a member of the popular family of algorithms known as Bug. A formal analysis of the planner is provided and several relevant properties of ABUG are identified. Besides, as done in some heuristic-based anytime approaches, we define bounds on the quality / length of the paths returned by the algorithm. Finally, in order to demonstrate the computational savings associated with the proposal, a comparative study involving a set of well-known path-planning techniques is also carried out.
    Advanced Robotics, 2009. ICAR 2009. International Conference on; 07/2009
  • A. Ortiz, J. Antich, G. Oliver
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    ABSTRACT: The surveillance and inspection of underwater installations such as telecommunication cables are currently carried out by trained operators who, from the surface, guide a Remotely Operated Vehicle (ROV) with cameras mounted over it. This manual visual control is, however, a very tedious job that tends to fail if the operator looses concentration. This paper describes a tracking system for underwater narrow telecommunication cables whose main objective is to allow an Autonomous Underwater Vehicle (AUV) to video-document the whole length of a cable. The approach is based on Particle Filters (PF) because of their natural ability to model multi-dimensional multi-modal probability density functions, what allows handling in a more appropriate way the ambiguities which naturally arise from undersea environments. The paper also describes a set of features added to the standard structure of a PF, which successfully compensate some large errors in the cable pose estimation when the non-enhanced tracker is applied. Extensive experimental results over a test set of more than 10,000 frames, for which a ground truth has been manually generated, have shown the usefulness of the solution proposed. Besides, results for a set of six video sequences accounting for almost 150,000 frames and around one hour and a half of successful continuous video tracking are also discussed. All those images come from inspection runs captured by ROVs navigating over real telecommunication undersea cables.
    OCEANS 2009 - EUROPE; 06/2009