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    Wyświetlanie 1-3 z 3
    Tytuł:
    A comprehensive aproach to teaching mobile robotics
    Autorzy:
    Chechliński, Ł.
    Koguciuk, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/385193.pdf
    Data publikacji:
    2017
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    teaching
    mobile robotics
    Opis:
    Mobile robotics can be an interesting subject for many students in a variety of engineering science fields. It builds a bridge between the pure theoretical digital world and the real, open environment. Several research results show that learning mobile robotics gives not only the ability to control certain types of robots but also develop many science-related atributes, technical and social skills. On the other hand, programming mobile robots is hard, and without a good guide, students are likely to lose their inspiration. For this purpose, we decided to develop a set of four exercises showing mobile robotics in the accessible and comprehensive way. The tasks were prepared for two types of wheeled robots: first equipped with a webcam, and second with sonar range finders. Both robots run using the ROS framework, as we find it the most popular robotics tool. The exercises are also designed considering the limited budget of educational institutions. Finally, guides for the tasks described in this paper have been shared on-line with the robotics community.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2017, 11, 3; 7-14
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Significance of features in object recognition using depth sensors
    Autorzy:
    Harasymowicz-Boggio, B.
    Chechlinski, L
    Siemiatkowska, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/173215.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    depth sensor
    RGB-D features
    3D object recognition
    Kinect
    Opis:
    This article concerns a key topic in the field of visual object recognition – the use of features. Object recognition algorithms typically rely on a fixed vector of pre-selected features extracted from 2D or 3D scenes, which are then analyzed with various classification techniques. On the other hand, the activation of particular features in biological vision systems is hierarchical and data-driven. To achieve a deeper understanding of the subject, we have introduced several mathematical tools to estimate multiple RGB-D features’ relevance for different object recognition tasks and conducted statistical experiments involving our database of high quality 3D point clouds. From the thorough analysis of the obtained results we draw conclusions that may be useful to design better, more adaptive object recognition algorithms.
    Źródło:
    Optica Applicata; 2015, 45, 4; 559-571
    0078-5466
    1899-7015
    Pojawia się w:
    Optica Applicata
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Semantic Place Labeling Method
    Autorzy:
    Siemiatkowska, B.
    Harasymowicz-Boggio, B.
    Chechlinski, Ł.
    Powiązania:
    https://bibliotekanauki.pl/articles/384729.pdf
    Data publikacji:
    2015
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    mapping
    classification
    Dempster-Shafer theory
    Opis:
    The paper presents a method of semantic localization of a mobile robot. The robot is equipped with a Sick laser finder and a Kinect sensor. The simplest source of informa tion about an environment is a scan obtained by the range sensor. The polygonal approximation of an observed area is performed. The shape of the polygon allows us to distinguish corridors from other places using a simple rule based system. During the next step rooms are classified based on objects which have been recognized. Each object votes for a set of classes of rooms. In a real environment we deal with uncertainty. Usually probabilistic theory is used to solve the problem but it is not capable of capturing subjective uncertainty. In our approach instead of the classic Bayesian method we proposed to perform classification using Dempster-Shafer theory (DST), which can be regarded as a generalization of the Bayesian theory and is able to deal with subjective uncertainty. The experiments performed in real office environment proved the efficiency of our approach.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2015, 9, 1; 28-33
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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