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    Wyświetlanie 1-7 z 7
    Tytuł:
    On augmenting the visual slam with direct orientation measurement using the 5-point algorithm
    Autorzy:
    Schmidt, A.
    Kraft, A.
    Fularz, M.
    Domagała, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/384310.pdf
    Data publikacji:
    2013
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    visual SLAM
    visual odometry
    Opis:
    This paper presents the attempt to merge two paradigms of the visual robot navigation: Visual Simultaneous Localization and Mapping (VSLAM) and Visual Odometry (VO). The VSLAM was augmented with the direct, visual measurement of the robot orientation change using the 5-point algorithm. The extended movement model of the robot was proposed and additional measurements were introduced to the SLAM system. The efficiency of the 5-point and 8-point algorithms was compared. The augmented system was compared with the state of the art VSLAM solution and the proposed modification allowed to reduce the tracking error by over 30%.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 1; 5-10
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The registration system for the evaluation of indoor visual slam and odometry algorithms
    Autorzy:
    Schmidt, A.
    Kraft, M.
    Fularz, M.
    Domagała, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/384854.pdf
    Data publikacji:
    2013
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    SLAM
    visual odometry
    benchmark
    Opis:
    This paper presents the new benchmark data registra- tion system aimed at facilitating the development and evaluation of the visual odometry and SLAM algorithms. The WiFiBOT LAB V3 wheeled robot equipped with three cameras, XSENS MTi atitude and heading reference system (AHRS) and Hall encoders can be used to gather data in indoor exploration scenarios. The ground truth trajectory of the robot is obtained using the visual motion tracking system. Additional static cameras simulating the surveillance network, as well as artificial markers augmen ting the navigation are incorporated in the system. The datasets registered with the presented system will be freely available for research purposes.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 2; 46-51
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the efficiency of population-based optimization in finding best parameters for RGB-D visual odometry
    Autorzy:
    Kostusiak, Aleksander
    Skrzypczyński, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/384397.pdf
    Data publikacji:
    2019
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    particle swarm optimization (PSO)
    evolutionary algorithm
    visual odometry
    RGB-D
    Opis:
    Visual odometry estimates the transformations between consecutive frames of a video stream in order to recover the camera’s trajectory. As this approach does not require to build a map of the observed environment, it is fast and simple to implement. In the last decade RGBD cameras proliferated in roboTIcs, being also the sensors of choice for many practical visual odometry systems. Although RGB-D cameras provide readily available depth images, that greatly simplify the frame-to-frame transformations computaTIon, the number of numerical parameters that have to be set properly in a visual odometry system to obtain an accurate trajectory estimate remains high. Whereas seƫng them by hand is certainly possible, it is a tedious try-and-error task. Therefore, in this article we make an assessment of two population-based approaches to parameter opTImizaTIon, that are for long time applied in various areas of robotics, as means to find best parameters of a simple RGB-D visual odometry system. The optimization algorithms investigated here are particle swarm optimization and an evolutionary algorithm variant. We focus on the optimization methods themselves, rather than on the visual odometry algorithm, seeking an efficient procedure to find parameters that minimize the estimated trajectory errors. From the experimental results we draw conclusions as to both the efficiency of the optimization methods, and the role of particular parameters in the visual odometry system.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 2; 5-14
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Implementacja algorytmu do estymacji ruchu własnego robota w układzie FPGA
    Implementation of the Robot Ego-Motion Estimation Algorithm in FPGA Circuits
    Autorzy:
    Kraft, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/156593.pdf
    Data publikacji:
    2011
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    FPGA
    odometria wizyjna
    system wizyjny
    system wbudowany
    visual odometry
    vision system
    embedded system
    Opis:
    W artykule opisano implementację w układzie FPGA systemu, realizującego zadanie szacowania ruchu własnego urządzenia (np. robota mobilnego), wyposażonego w pojedynczą kamerę. Zrealizowano ją w architekturze hybrydowej, sprzętowo-programowej. W artykule przedstawiono szczegółowy opis wynikowej architektury, jak również użycie zasobów układu programowalnego, oraz analizę wydajności systemu, wraz z porównaniem z alternatywnym rozwiązaniem opartym o komputer PC.
    The paper presents implementation of the robot ego-motion estimation algorithm in a single FPGA. The input data for the algorithm are feature correspondences detected in the image sequence registered by a single camera. The implemented system, based on the Microblaze microprocessor along with a dedicated hardware coprocessor, performs all stages of the algorithm - computation of the essential matrix using the 8-point algorithm employing singular value decomposition, robust estimation of the correct essential matrix using the RANSAC algorithm as well as computation of the rotation matrix and the translation vector (up to a scale) from the essential matrix [1, 2]. The system was implemented in a Virtex 5 PFGA and is capable of working with a clock speed of 100MHz. The microprocessor is used to find successive essential matrices using singular value decomposition. The solutions are tested for correctness using the coprocessor with the RANSAC algorithm [3]. The coprocessor employs a reduced, 23-bit floating point number representation to reduce resource usage. Upon successful completion of the essential matrix estimation, rotation and translation are computed. Additional sensors are used to deal with rotation and translation sign ambiguity. Table 1 presents the summary of resources used for implementation. Figure 1 outlines the system architecture. The results obtained are satisfactory and promising. The availability of inexpensive, low power, small footprint solution for ego-motion estimation is desirable for many applications.
    Źródło:
    Pomiary Automatyka Kontrola; 2011, R. 57, nr 1, 1; 6-8
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Experimental verification of a walking robot self - localization system with the kinect sensor
    Autorzy:
    Nowicki, M.
    Skrzypczyński, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/950763.pdf
    Data publikacji:
    2013
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    3D perception
    salient features
    iterative closest points
    visual odometry
    walking robot
    Opis:
    In this paper we investigate methods for self-localisation of a walking robot with the Kinect 3D active range sensor. The Iterative Closest Point (ICP) algorithm is considered as the basis for the computation of the robot rotation and translation between two viewpoints. As an alternative, a feature-based method for matching of 3D range data is considered, using the Normal Aligned Radial Feature (NARF) descriptors. Then, it is shown that NARFs can be used to compute a good initial estimate for the ICP algorithm, resulting in convergent estimation of the sensor egomotion. Experimental results are provided.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 4; 42-51
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Mathematical Model of Errors of Odometry and Georeferencing Channels in Visual Correlation Extreme Navigation
    Autorzy:
    Mukhina, Maryna Petrivna
    Kharchenko, Volodymyr Petrovych
    Powiązania:
    https://bibliotekanauki.pl/articles/503832.pdf
    Data publikacji:
    2017
    Wydawca:
    Międzynarodowa Wyższa Szkoła Logistyki i Transportu
    Tematy:
    correlation extreme navigation
    visual odometry
    geo-referencing
    feature matching
    cartographic errors
    dead reckoning errors
    Opis:
    The mathematic model of errors in correlation with the extreme navigation system (CENS) is developed basing on odometry and geo-referencing channels. The realization of the model is done in Simulink, and based on regular and random components of additive noise. The results of simulations prove accumulation of errors for odometry errors and its mitigation in case of geo-referencing in periods of correction.
    Źródło:
    Logistics and Transport; 2017, 33, 1; 31-36
    1734-2015
    Pojawia się w:
    Logistics and Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Efficient RGB-D data processing for feature-based self-localization of mobile robots
    Autorzy:
    Kraft, M.
    Nowicki, M.
    Penne, R.
    Schmidt, A.
    Skrzypczyński, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/330295.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    visual odometry
    simultaneous localization
    simultaneous mapping
    RGB-D
    tracking
    point features
    odometria wizyjna
    lokalizacja jednoczesna
    śledzenie
    Opis:
    The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a single RGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previous results as to the general architecture, the important novel elements introduced here are aimed at improving the precision and robustness of the motion estimate computed from the matching point features of two RGB-D frames. Moreover, we demonstrate that the visual odometry system can serve as the front-end for a pose-based simultaneous localization and mapping solution. The proposed solutions are tested on publicly available data sets to ensure that the results are scientifically verifiable. The experimental results demonstrate gains due to the improved feature extraction and management mechanisms, whereas the performance of the whole navigation system compares favorably to results known from the literature.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2016, 26, 1; 63-79
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-7 z 7

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