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Abstract
  • The usage of articulated tools for autonomous
    robots is still a challenging task. One of the difficulties is to
    automatically estimate the tool’s kinematics model. This model
    cannot be obtained from a single passive observation, because
    some information, such as a rotation axis (hinge), can only be
    detected when the tool is being used. Inspired by a baby using
    its hands while playing with an articulated toy, we employ a
    dual arm robotic setup and propose an interactive manipulation
    strategy based on visual-tactile servoing to estimate the tool’s
    kinematics model.
    In our proposed method, one hand is holding the tool’s
    handle stably, and the other arm equipped with tactile finger
    flips the movable part of the articulated tool. An innovative
    visuo-tactile servoing controller is introduced to implement
    the flipping task by integrating the vision and tactile feed-
    back in a compact control loop. In order to deal with the
    temporary invisibility of the movable part in camera, a data
    fusion method which integrates the visual measurement of the
    movable part and the fingertip’s motion trajectory is used to
    optimally estimate the orientation of the tool’s movable part.
    The important tool’s kinematic parameters are estimated by
    geometric calculations while the movable part is flipped by the
    finger.
    We evaluate our method by flipping a pivoting cleaning
    head (flap) of a wiper and estimating the wiper’s kinematic
    parameters. We demonstrate that the flap of the wiper is flipped
    robustly, even the flap is shortly invisible. The orientation of
    the flap is tracked well compared to the ground truth data. The
    kinematic parameters of the wiper are estimated correctly
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