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Design of intelligent 3D collaborative manufacturing platform for non-holonomic mobile industrial robots based on improved binocular vision

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Abstract

The complexity of industrial production line of non-integrated mobile industrial robot is high, which leads to the deviation of industrial robot trajectory and low working accuracy, which further affects the production progress. In order to improve the stability of industrial robots, the design of intelligent three-dimensional collaborative manufacturing platform for nonholonomic mobile industrial robots based on improved binocular vision is proposed. ARM controller, data transmission and communication module, PLC control module and PLC input and output wiring module are designed, and the four functional modules work in coordination to realize accurate perception of the working area. A binocular vision model based on texture image and 3D point cloud registration is constructed. The trajectory of nonholonomic mobile industrial robot is obtained by fuzzy function estimation and variational function, and the object posture is recognized. The intelligent 3D collaborative manufacturing platform of mobile industrial robot is designed by combining the intelligent 3D collaborative manufacturing technology. The test results show that the proposed method has better trajectory control effect, better sequencing performance and better robustness. It shows that this method can effectively control nonholonomic mobile industrial robots.

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The data used to support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

The study was supported by “Sub project of National key R&D plan: Research on Key Technologies of high load adaptive variable curvature facade maintenance robot (Grant No. 2018YFB1309401)”.

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Correspondence to Wentao Mei.

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Mei, W., Zheng, Y. & Gu, Y. Design of intelligent 3D collaborative manufacturing platform for non-holonomic mobile industrial robots based on improved binocular vision. Int J Intell Robot Appl 7, 740–751 (2023). https://doi.org/10.1007/s41315-023-00293-z

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  • DOI: https://doi.org/10.1007/s41315-023-00293-z

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