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  • 1.
    Baerveldt, Albert-Jan
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    A vision system for object verification and localization based on local features2001In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 34, no 2-3, p. 83-92Article in journal (Refereed)
    Abstract [en]

    An object verification and localization system should answer the question whether an expected object is present in an image or not, i.e. verification, and if present where it is located. Such a system would be very useful for mobile robots, e.g. for landmark recognition or for the fulfilment of certain tasks. In this paper, we present an object verification and localization system specially adapted to the needs of mobile robots. The object model is based on a collection of local features derived from a small neighbourhood around automatically detected interest points. The learned representation of the object is then matched with the image under consideration. The tests, based on 81 images, showed a very satisfying tolerance to scale changes of up to 50%, to viewpoint variations of 20, to occlusion of up to 80% and to major background changes as well as to local and global illumination changes. The tests also showed that the verification capabilities are very good and that similar objects did not trigger any false verification.

  • 2.
    Baerveldt, Albert-Jan
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Arras, Kai Oliver
    EPFL, Lausanne, Switzerland.
    Balkenius, Christian
    Lund University, Lund, Sweden.
    Editorial2003In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 44, no 1, p. 100p. 1-Article in journal (Other (popular science, discussion, etc.))
  • 3.
    Bengtsson, Ola
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Baerveldt, Albert-Jan
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Robot localization based on scan-matching - estimating the covariance matrix for the IDC algorithm2003In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 44, no 1, p. 29-40Article in journal (Refereed)
    Abstract [en]

    We have previously presented a new scan-matching algorithm based on the IDC (iterative dual correspondence) algorithm, which showed a good localization performance even in environments with severe changes. The problem of the IDC algorithm is that there is no good way to estimate a covariance matrix of the position estimate, which prohibits an effective fusion with other position estimates of other sensors. This paper presents two new ways to estimate the covariance matrix. The first estimates the covariance matrix from the Hessian matrix of the error function minimized by the scan-matching algorithm. The second one, which is an off-line method, estimates the covariance matrix of a specific scan, from a specific position by simulating and matching scans around the position. Simulation results show that the covariance matrix provided by the off-line method fully corresponds with the real one. Some preliminary tests on real data indicate that the off-line method gives a good quality value of a specific scan position, which is of great value in map building.

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