Proximity and distance estimation sensors are broadly used in robotic hands to enhance the quality of grasping during grasp planning, grasp correction and in-hand manipulation. This paper presents a fiber optical proximity sensor that is integrated with a tactile sensing fingertip of a robotic hand of a mobile robot. The distance estimation of proximity sensors are typically influenced by the reflective properties of an object, such as color or surface roughness. With the approach proposed in this paper, the accuracy of the proximity sensor is enhanced using the information collected by the vision system of the robot. A camera is employed to obtain RGB values of the object to be grasped. Further on, the data obtained from the camera is used to obtain the correct calibration for the proximity sensor. Based on the experimental evidence, it is shown that our approach can be effectively used to reduce the distance estimation error.


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    Titel :

    Fingertip Proximity Sensor with Realtime Visual-based Calibration


    Beteiligte:
    Konstantinova, J (Autor:in) / Stilli, A (Autor:in) / Faragasso, A (Autor:in) / Althoefer, K (Autor:in)

    Erscheinungsdatum :

    2016-01-01


    Anmerkungen:

    In: Proceedings of 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). (pp. pp. 170-175). IEEE: Daejeon, South Korea. (2016)


    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629



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