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Multi-robot coverage path planning for dimensional inspection of large free-form surfaces based on hierarchical optimization

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Abstract

The multi-robot coverage path planning problem (MRCPP), incorporating with the sub-problems of viewpoint sampling, viewpoint task allocation and robotic sequential planning generally, is a highly coupled problem with complex engineering constraints and is difficult to achieve the optimal result. Most coverage path planning studies in the field of industrial inspection focus on viewpoint sampling and sequential path planning for the individual robot. At the same time, the measurement uncertainty requirements of the inspected surface features for the candidate viewpoints are rarely considered in the process of CPP. To address this problem, a systematic MRCPP framework for free-form surface inspection is developed considering the measurement uncertainty requirements and full coverage of the surfaces to ensure the inspection efficiency and the scanning accuracy of to-be-inspect features. Specifically, a stepwise method for multi-robot optical coverage path planning is proposed. Firstly, a redundant viewpoint set is generated based on the geometric model of the product; additionally, considering the constraints of measurement uncertainty and full coverage constraint, an enhanced Random Inspection Tree Algorithm (RITA) is used to obtain the optimal viewpoint set. Secondly, an improved group Ant Colony optimization (IACO) algorithm is proposed to realize multi-robot viewpoint allocation and sequential planning on the optimal viewpoint set. Finally, in order to evaluate the effectiveness of the proposed method, a 4-robot optical inspection case of an auto body was used. Compared to the benchmark method, the number of viewpoints is reduced by 56.38%, and the bottleneck time in the station is reduced by 7.651%.

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Funding

Dr. Liu was partially funded by the National Natural Science Foundation of China (51875362), the Natural Science Foundation of Shanghai (21ZR1444500), and the Shanghai Pujiang Program (22PJD048).

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Authors and Affiliations

  1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Wenzheng Zhao, Yinhua Liu, Yanzheng Li & Chengwei Hu

  2. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Rui Sun

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  1. Wenzheng Zhao
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  2. Yinhua Liu
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  3. Yanzheng Li
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  4. Chengwei Hu
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  5. Rui Sun
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Contributions

All authors contributed to the study conception and design. Conceptualization of this study was performed by Wenzheng Zhao, Yinhua Liu, Yanzheng Li, Chengwei Hu, and Rui Sun. Methodology, software, and first draft were completed by Wenzheng Zhao, Yinhua Liu, and Yanzheng Li. Draft revision and finalization were performed by Wenzheng Zhao, Chengwei Hu, and Rui Sun. All authors read and approved the final manuscript.

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Correspondence to Yinhua Liu.

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Zhao, W., Liu, Y., Li, Y. et al. Multi-robot coverage path planning for dimensional inspection of large free-form surfaces based on hierarchical optimization. Int J Adv Manuf Technol 127, 5471–5486 (2023). https://doi.org/10.1007/s00170-023-11788-1

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