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Intelligent welding robot path optimization based on discrete elite PSO

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Abstract

Rational path optimization of weld joints sequence can reduce welding time, improve the welding quality and productivity in robot welding process, especially when the number of weld joints is large. In this article, definition of welding robot path optimization is studied first. Then, PSO is used to solve welding robot path optimization after algorithm discretization and global optimization capability improvement based on elite strategy. The shortest path length and welding deformation were considered as the optimization criteria. For double welding robot welding path optimization, the influence with each other should be avoided for two welding robots. Hence, an optimization strategy was proposed to solve double welding robots path optimization problem with constrains of avoiding mutual influence. Simulation results show that the proposed optimization algorithm and strategy can promise desired optimization effect.

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Acknowledgments

The authors appreciate the support of Shanghai Natural Science Foundation (14ZR1409900), and National Natural Science Foundation of China (61573144).

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Authors and Affiliations

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China

    Xuewu Wang, Yingpan Shi, Yixin Yan & Xingsheng Gu

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  1. Xuewu Wang
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  2. Yingpan Shi
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  3. Yixin Yan
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  4. Xingsheng Gu
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Corresponding author

Correspondence to Xuewu Wang.

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Funding

This study was funded by Shanghai Natural Science Foundation (Grant Number 14ZR1409900), and National Natural Science Foundation of China (Grant Number 61573144).

Conflict of interest

All authors declare that they have no conflict of interest.

Additional information

Communicated by Y. Jin.

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Cite this article

Wang, X., Shi, Y., Yan, Y. et al. Intelligent welding robot path optimization based on discrete elite PSO. Soft Comput 21, 5869–5881 (2017). https://doi.org/10.1007/s00500-016-2121-2

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  • DOI: https://doi.org/10.1007/s00500-016-2121-2

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