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Planar contour tracking in the presence of pose and model errors by Kalman filtering techniques

Mihaylova, L. and Bruyninckx, H. and De Schutter, J. and Staffetti, E. (2001) Planar contour tracking in the presence of pose and model errors by Kalman filtering techniques. In: Multisensor Fusion and Integration for Intelligent Systems, 2001. MFI 2001. International Conference on :. , pp. 329-334.

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    The paper presents a solution to the problem of planar contour tracking with a force-controlled robot. The contour shape is unknown and is characterized at each time step by the curvature together with the orientation angle and arc length. The unknown contour curvature, continuously changing, is supposed to be within a preliminary given interval. An Interacting Multiple Model (IMM) filter is implemented to cope with the uncertainties. The interval of possible curvature values is discretized, i.e., a grid is formed and several Extended Kalman filters (EKFs) are run in parallel. The curvature estimate represents a fusion of the values from the grid with the IMM probabilities. The orientation angle estimate is also a fusion of the estimates, obtained from the separate Kalman filters with the mode probabilities. A single-model EKF is implemented to localize the unknown initial robot end-effector position over the contour. The performance of both algorithms is investigated and results, based on real data, are presented.

    Item Type: Contribution in Book/Report/Proceedings
    Additional Information: pp. 329-334 doi:10.1109/MFI.2001.1013556
    Uncontrolled Keywords: estimation ; robotics ; IMM filter ; model and noise uncertainties ; Kalman filter ; force control DCS-publications-id ; inproc-441 ; DCS-publications-credits ; dsp-fa ; DCS-publications-personnel-id ; 121
    Subjects: ?? qa75 ??
    Departments: Faculty of Science and Technology > School of Computing & Communications
    ID Code: 1376
    Deposited By: Dr L Mihaylov
    Deposited On: 08 Feb 2008 09:24
    Refereed?: No
    Published?: Published
    Last Modified: 18 Jul 2018 01:14
    Identification Number:

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