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

被引：7

作者：

Wu, Zhou ^{[1
]}

Wu, Junjun ^{[1
]}

Zhao, Mingbo ^{[2
]}

Feng, Liang ^{[3
]}

Liu, Kai ^{[3
]}

机构：

[1] Chongqing Univ, Sch Automat, Chongqing, Peoples R China

[2] Donghua Univ, Sch Informat Sci & Technol, Shanghai, Peoples R China

[3] Chongqing Univ, Sch Comp Sci, Chongqing, Peoples R China

来源：

NEURAL COMPUTING & APPLICATIONS | 2021年 / 33卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Ant colony system; k-means clustering; 3D printer; Laser engraving; Travelling salesman problem; Trajectory optimization; Robot; OPTIMIZATION ALGORITHM; PATH OPTIMIZATION;

D O I：

10.1007/s00521-020-05468-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

下载

页码：6939 / 6949

页数：11

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