Precise grasp is a vital application in robot manipulation while real-time slip detection can help the control system to monitor grasp force and compensate for position deviation. However, commonly-used robots hardly have slip detection modules, and the lack of real-time slip information obstructs the robot from making timely force or position adjustments. This paper proposes a real-time slip detection method using 2D images and surface height maps provided by a tactile sensor. Marker-centered sub-height maps, which indicate the local tangential and normal deformation of the sensor surface, are compared based on fast normalized cross correlation (NCC). The object status is determined from the integration of all the local slips. The experiment validates the proposed method with the average classification accuracy of 88.89% for 21 daily objects in 90 grasp trials, including translational slip, rotational slip, and stable trials. Frame detection accuracy of 94.56% for slip frames and 98.81% for stable frames are achieved. The real-time capability of the algorithm is also tested. The proposed method demonstrates the feasibility of detecting slip using the dual-modal outputs from single tactile sensor which can be installed on robot grippers. Moreover, real-time classification results can be used to monitor force or position regulation strategies and assist precise manipulation, including assembly work and deformable objects operation.


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    Title :

    Tactile-Based Slip Detection Towards Robot Grasping


    Additional title:

    Lect.Notes Computer


    Contributors:
    Yang, Huayong (editor) / Liu, Honghai (editor) / Zou, Jun (editor) / Yin, Zhouping (editor) / Liu, Lianqing (editor) / Yang, Geng (editor) / Ouyang, Xiaoping (editor) / Wang, Zhiyong (editor) / Gong, Yuru (author) / Xing, Yan (author)

    Conference:

    International Conference on Intelligent Robotics and Applications ; 2023 ; Hangzhou, China July 05, 2023 - July 07, 2023



    Publication date :

    2023-10-16


    Size :

    15 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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