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Neural Computing and Applications

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18-11-2020 | Original Article

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

Published in: Neural Computing and Applications | Issue 12/2021

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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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Title: Two-layered ant colony system to improve engraving robot’s efficiency based on a large-scale TSP model
Publication date: 18-11-2020
Published in: Neural Computing and Applications / Issue 12/2021
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-020-05468-4

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