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An automatic modeling method for modular reconfigurable robots based on model identification

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Abstract

Modular reconfigurable robots (MRRs) have high reconfigurability and can meet the needs of customized production in modern manufacturing. After each MRR is assembled, the reprogramming process frequently requires time-consuming and expensive professional work. The wide applications of MRRs call for automatic reprogramming methods. In this research, an automatic framework is proposed for solving the MRR modeling problem based on the D–H (Denavit–Hartenberg) convention and dynamic parameter identification. Simulations and experiments are conducted on AUBO I-series modular robots. Three other existing modeling algorithms are adopted to make comparison with the proposed one. It is verified that the proposed framework can achieve the desired automatic modeling process with higher accuracy. Specifically, the accuracy of dynamic parameter identification is enhanced by more than 23% in typical experimental scenarios.

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Funding

This work was partially supported by National Key R &D Program of China (2019YFB1309900).

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Authors and Affiliations

  1. School of Mechanical Engineering and Automation, BeiHang University, Beijing, 100083, China

    Zeyu Li & Hongxing Wei

  2. AUBO (Beijing) Robotics Technology CO., LTD, Beijing, China

    Ziyi Yuan & Gang Liu

Authors
  1. Zeyu Li
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  2. Hongxing Wei
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  3. Ziyi Yuan
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  4. Gang Liu
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by ZL, ZY and GL. The first draft of the manuscript was written by ZL and extended by HW. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Zeyu Li.

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Li, Z., Wei, H., Yuan, Z. et al. An automatic modeling method for modular reconfigurable robots based on model identification. Intel Serv Robotics 16, 61–73 (2023). https://doi.org/10.1007/s11370-023-00453-x

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  • DOI: https://doi.org/10.1007/s11370-023-00453-x

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