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  • 1.
    Albitar, Houssam
    et al.
    Örebro University, School of Science and Technology.
    Dandan, Kinan
    Örebro University, School of Science and Technology.
    Ananiev, Anani
    Örebro University, School of Science and Technology.
    Kalaykov, Ivan
    Örebro University, School of Science and Technology.
    Underwater Robotics: Surface Cleaning Technics, Adhesion and Locomotion Systems2016In: International Journal of Advanced Robotic Systems, ISSN 1729-8806, E-ISSN 1729-8814, Vol. 13, article id 7Article in journal (Refereed)
    Abstract [en]

    Underwater robots are being developed for various applications ranging from inspection to maintenance and cleaning of submerged surfaces and constructions. These platforms should be able to travel on these surfaces. Furthermore, these platforms should adapt and reconfigure for underwater environment conditions and should be autonomous. Regarding the adhesion to the surface, they should produce a proper attaching force using a light-weight technics. Taking these facts into consideration, this paper presents a survey of different technologies used for underwater cleaning and the available underwater robotics solutions for the locomotion and the adhesion to surfaces.

  • 2.
    Dandan, Kinan
    et al.
    Örebro University, School of Science and Technology.
    Albitar, Houssam
    Örebro University, School of Science and Technology.
    Ananiev, Anani
    Örebro University, School of Science and Technology.
    Kalaykov, Ivan
    Örebro University, School of Science and Technology.
    Motion Control of Siro: The Silo Cleaning Robot2015In: International Journal of Advanced Robotic Systems, ISSN 1729-8806, E-ISSN 1729-8814, Vol. 12, article id 184Article in journal (Refereed)
    Abstract [en]

    Both the principle of operation and the motion-control system of a suspended robot for surface cleaning in silos are presented in this paper. The mechanical design is a reasonable compromise between basically contradictory factors in the design: the small entrance and the large surface of the confined space, and the suspension and the stabilization of the robot. The design consists of three main parts: a support unit, the cleaning robot and a cleaning mechanism. The latter two parts enter the silo in a folded form and, thereafter, the robot’s arms are spread in order to achieve stability during the cleaning process. The vertical movement of the robot is achieved via sequential crawling motions.

    The control system is divided into two separate subsystems, the robot’s control subsystem and a support-unit control subsystem, in order to facilitate different operational modes. The robot has three principle motion-control tasks: positioning the robot inside the silo, holding a vertical position during the cleaning process and a crawling movement.

    A scaled prototype of the robot has been implemented and tested to prove the concept, in order to make certain that the mechanical design suits the main functions of the robotic system, to realize the robot’s design in an industrial version and to test it in a realistic environment.

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  • 3.
    Persson, Andreas
    et al.
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Fast Matching of Binary Descriptors for Large-scale Applications in Robot Vision2016In: International Journal of Advanced Robotic Systems, ISSN 1729-8806, E-ISSN 1729-8814, Vol. 13, article id 58Article in journal (Refereed)
    Abstract [en]

    The introduction of computationally efficient binary feature descriptors has raised new opportunities for real-world robot vision applications. However, brute force feature matching of binary descriptors is only practical for smaller datasets. In the literature, there has therefore been an increasing interest in representing and matching binary descriptors more efficiently. In this article, we follow this trend and present a method for efficiently and dynamically quantizing binary descriptors through a summarized frequency count into compact representations (called fsum) for improved feature matching of binary pointfeatures. With the motivation that real-world robot applications must adapt to a changing environment, we further present an overview of the field of algorithms, which concerns the efficient matching of binary descriptors and which are able to incorporate changes over time, such as clustered search trees and bag-of-features improved by vocabulary adaptation. The focus for this article is on evaluation, particularly large scale evaluation, compared to alternatives that exist within the field. Throughout this evaluation it is shown that the fsum approach is both efficient in terms of computational cost and memory requirements, while retaining adequate retrieval accuracy. It is further shown that the presented algorithm is equally suited to binary descriptors of arbitrary type and that the algorithm is therefore a valid option for several types of vision applications.

  • 4.
    Simoens, Pieter
    et al.
    IDLab, Ghent University – imec, Ghent, Belgium.
    Dragone, Mauro
    Research Institute of Signals, Sensors and Systems (ISSS), Heriot-Watt University, Edinburgh, United Kingdom.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    The Internet of Robotic Things: A review of concept, added value and applications2018In: International Journal of Advanced Robotic Systems, ISSN 1729-8806, E-ISSN 1729-8814, Vol. 15, no 1, article id 1729881418759424Article, review/survey (Refereed)
    Abstract [en]

    The Internet of Robotic Things is an emerging vision that brings together pervasive sensors and objects with robotic and autonomous systems. This survey examines how the merger of robotic and Internet of Things technologies will advance the abilities of both the current Internet of Things and the current robotic systems, thus enabling the creation of new, potentially disruptive services. We discuss some of the new technological challenges created by this merger and conclude that a truly holistic view is needed but currently lacking.

    Download full text (pdf)
    The Internet of Robotic Things: A review of concept, added value and applications
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