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Quantitative motion detection of in-hand objects for robotic grasp manipulation

Xueyong Li, Kai Zhao, Changhou Lu, Yonghui Wang

Year
2019
Citations
3
Access
Open access

Abstract

In an actual grasp operation, grasp accidents (slant, rolling, turning over, and dropping) of in-hand objects occur frequently. Quantitative motion detection of in-hand objects is critical to optimize the grasp configuration and to improve the stability and dexterity of a grasp manipulation. In this article, an innovative method for quantitative measurement of the motions of in-hand objects is presented. Firstly, the slip information at object–finger interface between adjacent states is detected by three omnidirectional slip sensors; next, singular value decomposition method is applied to calculate the rotation and translation matrices according to the relative coordinate changes extracted from the slip information. Finally, Euler angles and the linear displacements which illustrate the motion of in-hand objects are quantitatively measured from the translation matrix and the rotation matrix, and the continuous motion track can be further established. Experiment results show that the proposed method is effective in detecting multiple motion information of in-hand objects.

Keywords

GRASPComputer scienceComputer visionArtificial intelligenceSlip (aerodynamics)Rotation (mathematics)Singular value decompositionMotion (physics)Translation (biology)Rotation matrix

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