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Automatic single-view monocular camera calibration-based object manipulation using novel dexterous multi-fingered delta robot

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Abstract

The approximation of 3D geometry through single image is a particular instance of 3D reconstruction from several images. The advance information or user input should be provided to retrieve or conclude depth information. This research presents a novel automatic method to enumerated 3D affine measurements from a single perspective image. The least geometric information has been resolute through the image of the scene. The vanishing line and a vanishing point are two required information to reconstruct from an image of a scene. The affine scene structure can be reconstructed through the image of a scene. The proposed approach has many advantages; there is no need of the camera’s intrinsic matrix and the explicit correlation among camera and scene (pose), no need for selecting Vx, Vy, Vz points, novel dexterous robot architecture for manipulation. In this paper, the following approaches have been implemented: (1) the three sets of vanishing points in X, Y, and Z axis; (2) the vanishing lines of the image; (3) distance among planes that parallel to the reference plane; (4) image wrapping; (5) corner detection (algorithm has been implemented in order to make the process automatic). The indigenous data set has been taken for the experiment. The results are compared with Zhang- and ArUco-based calibration. This novel approach has been used to perform tracking and manipulation of an object in real-time environment.

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  1. Mechanical Engineering Department, Indian Institute of Technology Delhi, New Delhi, India

    Sachin Kansal & Sudipto Mukherjee

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  1. Sachin Kansal
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  2. Sudipto Mukherjee
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Correspondence to Sachin Kansal.

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Kansal, S., Mukherjee, S. Automatic single-view monocular camera calibration-based object manipulation using novel dexterous multi-fingered delta robot. Neural Comput & Applic 31, 2661–2678 (2019). https://doi.org/10.1007/s00521-017-3221-3

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  • DOI: https://doi.org/10.1007/s00521-017-3221-3

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