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作者:

Yu, Jianjun (Yu, Jianjun.) | Wang, Yang (Wang, Yang.) | Ruan, Xiaogang (Ruan, Xiaogang.) | Zuo, Guoyu (Zuo, Guoyu.) (学者:左国玉) | Li, Chen (Li, Chen.)

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EI

摘要:

In order to save time and reduce the energy loss of the AGV when transporting the objects, the discrete cuckoo algorithm is used to solve the path planning problem of multi targets points. Firstly, the cuckoo algorithm is applied to the path planning of the AGV single target point based on the grip map, and the optimal path of the AGV to each object and the optimal path of each object to the specified position are obtained. Secondly, discretizing the cuckoo algorithm, and in the process of discretization, multiple operators such as reverse sequence, insertion, substitution and double bridge are combined into different neighborhood structures, which will used to find the optimal solution through Levi flight mechanism. Finally, the discrete cuckoo algorithm is used to generate the global optimal path for AGV to transport multiple objects. Simulation results show that the proposed algorithm successfully solves the multi-target point path planning problem of AGV. Compared with other algorithms, the proposed algorithm can avoid partial optimality and achieve fast convergence speed. © 2019 IEEE.

关键词:

Automatic guided vehicles Automation Energy dissipation Motion planning

作者机构:

  • [ 1 ] [Yu, Jianjun]Beijing University of Technology, Faculty of Information Technology, China
  • [ 2 ] [Yu, Jianjun]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 3 ] [Wang, Yang]Beijing University of Technology, Faculty of Information Technology, China
  • [ 4 ] [Wang, Yang]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 5 ] [Ruan, Xiaogang]Beijing University of Technology, Faculty of Information Technology, China
  • [ 6 ] [Ruan, Xiaogang]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 7 ] [Zuo, Guoyu]Beijing University of Technology, Faculty of Information Technology, China
  • [ 8 ] [Zuo, Guoyu]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 9 ] [Li, Chen]Beijing University of Technology, Faculty of Information Technology, China
  • [ 10 ] [Li, Chen]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China

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年份: 2019

页码: 556-561

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 3

ESI高被引论文在榜: 0 展开所有

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