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Two-layered ant colony system to improve engraving robot’s efficiency based on a large-scale TSP model

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Abstract

Laser engraving is an essential tool of automatic drawings and 3D printers. When the laser engraving tasks become large and complicated, engraving process will be time-consuming. To improve the time and energy efficiency, the trajectory optimization of laser engraving is studied. The trajectory of laser engraving robot is modelled as a large-scale traveling salesman problem (TSP), by converting grayscale images into halftone images. To solve the large-scale TSP, two-layered ant colony system (ACS) is newly proposed to combine k-means, top-layer ACS, and bottom-layer ACS. Finally, we use the presented algorithm to optimize the path of four engraving instances which include tens of thousands of discrete points. Experimental results show that this method can reduce laser engraving time by about 50% compared with traditional engraving methods.

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Funding

Funding was provided by the National Natural Science Foundation of China (Project No. 61803054, 61971121, 61872049, 61876025), the Fundamental Research Funds for the Central Universities (2019CDQYZDH030).

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Authors and Affiliations

  1. School of Automation, Chongqing University, ChongQing, China

    Zhou Wu & Junjun Wu

  2. School of Information Science and Technology, Donghua University, Shanghai, China

    Mingbo Zhao

  3. School of Computer Science, Chongqing University, Chongqing, China

    Liang Feng & Kai Liu

Authors
  1. Zhou Wu
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  2. Junjun Wu
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  3. Mingbo Zhao
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  4. Liang Feng
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  5. Kai Liu
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Correspondence to Zhou Wu.

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Wu, Z., Wu, J., Zhao, M. et al. Two-layered ant colony system to improve engraving robot’s efficiency based on a large-scale TSP model. Neural Comput & Applic 33, 6939–6949 (2021). https://doi.org/10.1007/s00521-020-05468-4

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