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Precise pose and assembly detection of generic tubular joints based on partial scan data

  • Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems
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Abstract

Intelligent and accurate determination of the position and orientation, or pose, of a workpiece which is manually placed is essential for automating fabrication tasks such as welding. In this paper, a novel algorithm based on minimizing the area of a boundary enclosing partial scan data points is proposed for detecting both the pose and assembly of tubular joints with the aid of reference ideal models. The proposed algorithm can also be applied to tubular joints with non-cylindrical cross sections. The fit-up information obtained can be used to determine whether realignment is required or combined with the pose information to re-plan paths for subsequent tasks. The focus of existing state-of-the-art is on objects with features, and the localization of featureless objects such as generic tubular joints using partial and sparse scan data remains a challenge. The proposed algorithm is applied to an actual robotic welding system to locate a tubular workpiece. Experiment results using the scan data as ground truth show that root mean square error is less than 1% of the pipe diameters, considering both brace and chord components with diameters greater than 200 mm.

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Acknowledgements

The authors thank the National Research Foundation, Keppel Corporation and National University of Singapore for supporting this work done in the Keppel-NUS Corporate Laboratory. The conclusions put forward reflect the views of the authors alone and not necessarily those of the institutions within the Corporate Laboratory.

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Authors and Affiliations

  1. Engineering Cluster, Singapore Institute of Technology, Singapore, Singapore

    Chee Khiang Pang

  2. Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore

    Yan Zhi Tan & Chee Meng Chew

  3. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Abdullah Al Mamun

  4. Keppel Technology and Innovation, Singapore, Singapore

    Fook Seng Wong

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  1. Yan Zhi Tan
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  2. Chee Khiang Pang
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  3. Abdullah Al Mamun
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Correspondence to Chee Khiang Pang.

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Tan, Y.Z., Pang, C.K., Al Mamun, A. et al. Precise pose and assembly detection of generic tubular joints based on partial scan data. Neural Comput & Applic 34, 5201–5211 (2022). https://doi.org/10.1007/s00521-021-06246-6

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  • DOI: https://doi.org/10.1007/s00521-021-06246-6

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