An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots

Xin Yao; Xiaojun Shi; Xiaodong Zhang; Xuesong Mei

doi:10.1109/AEECA55500.2022.9918906

An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots

Xin Yao
, Xiaojun Shi
, Xiaodong Zhang
, Xuesong Mei

School of Mechanical Engineering

Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Ant Colony optimization (ACO) has been widely used in mobile robot path planning in recent years. The parameters of ACO have great influence on the global search ability and convergence speed of the algorithm. The existing parameter tuning methods of the ACO mostly depends on experience or cannot evaluate the interaction between parameters, which make it very time-consuming and difficult to obtain excellent parameter combination. An experimental design method Uniform Design (UD) is applied for the ACO offline tuning of mobile robot path planning algorithm in this paper. The results show that the UD method can rapidly obtain excellent parameter combination from few of experiment simulation. The simulation results and experimental results show that the optimal parameter combination of ACO obtained by the UD method can rank in the top 10% of the valid results of the enumeration method sorted by the path length. In addition, the algorithm running time of the optimal parameter combination is shorter than that of most parameter combinations obtained by enumeration method.

Original language	English
Title of host publication	2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1183-1191
Number of pages	9
ISBN (Electronic)	9781665480901
DOIs	https://doi.org/10.1109/AEECA55500.2022.9918906
State	Published - 2022
Event	2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022 - Dalian, China Duration: 20 Aug 2022 → 21 Aug 2022

Publication series

Name	2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022

Conference

Conference	2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022
Country/Territory	China
City	Dalian
Period	20/08/22 → 21/08/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

ant colony optimization
parameter tuning
path planning
uniform design

Access to Document

10.1109/AEECA55500.2022.9918906

Cite this

Yao, X., Shi, X., Zhang, X., & Mei, X. (2022). An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots. In 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022 (pp. 1183-1191). (2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AEECA55500.2022.9918906

Yao, Xin ; Shi, Xiaojun ; Zhang, Xiaodong et al. / An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots. 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 1183-1191 (2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022).

@inproceedings{410cb529a3bb47078366ab07175c8ce4,

title = "An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots",

abstract = "Ant Colony optimization (ACO) has been widely used in mobile robot path planning in recent years. The parameters of ACO have great influence on the global search ability and convergence speed of the algorithm. The existing parameter tuning methods of the ACO mostly depends on experience or cannot evaluate the interaction between parameters, which make it very time-consuming and difficult to obtain excellent parameter combination. An experimental design method Uniform Design (UD) is applied for the ACO offline tuning of mobile robot path planning algorithm in this paper. The results show that the UD method can rapidly obtain excellent parameter combination from few of experiment simulation. The simulation results and experimental results show that the optimal parameter combination of ACO obtained by the UD method can rank in the top 10\% of the valid results of the enumeration method sorted by the path length. In addition, the algorithm running time of the optimal parameter combination is shorter than that of most parameter combinations obtained by enumeration method.",

keywords = "ant colony optimization, parameter tuning, path planning, uniform design",

author = "Xin Yao and Xiaojun Shi and Xiaodong Zhang and Xuesong Mei",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022 ; Conference date: 20-08-2022 Through 21-08-2022",

year = "2022",

doi = "10.1109/AEECA55500.2022.9918906",

language = "英语",

series = "2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1183--1191",

booktitle = "2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022",

}

Yao, X, Shi, X, Zhang, X & Mei, X 2022, An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots. in 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022. 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022, Institute of Electrical and Electronics Engineers Inc., pp. 1183-1191, 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022, Dalian, China, 20/08/22. https://doi.org/10.1109/AEECA55500.2022.9918906

An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots. / Yao, Xin; Shi, Xiaojun; Zhang, Xiaodong et al.
2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 1183-1191 (2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots

AU - Yao, Xin

AU - Shi, Xiaojun

AU - Zhang, Xiaodong

AU - Mei, Xuesong

PY - 2022

Y1 - 2022

N2 - Ant Colony optimization (ACO) has been widely used in mobile robot path planning in recent years. The parameters of ACO have great influence on the global search ability and convergence speed of the algorithm. The existing parameter tuning methods of the ACO mostly depends on experience or cannot evaluate the interaction between parameters, which make it very time-consuming and difficult to obtain excellent parameter combination. An experimental design method Uniform Design (UD) is applied for the ACO offline tuning of mobile robot path planning algorithm in this paper. The results show that the UD method can rapidly obtain excellent parameter combination from few of experiment simulation. The simulation results and experimental results show that the optimal parameter combination of ACO obtained by the UD method can rank in the top 10% of the valid results of the enumeration method sorted by the path length. In addition, the algorithm running time of the optimal parameter combination is shorter than that of most parameter combinations obtained by enumeration method.

AB - Ant Colony optimization (ACO) has been widely used in mobile robot path planning in recent years. The parameters of ACO have great influence on the global search ability and convergence speed of the algorithm. The existing parameter tuning methods of the ACO mostly depends on experience or cannot evaluate the interaction between parameters, which make it very time-consuming and difficult to obtain excellent parameter combination. An experimental design method Uniform Design (UD) is applied for the ACO offline tuning of mobile robot path planning algorithm in this paper. The results show that the UD method can rapidly obtain excellent parameter combination from few of experiment simulation. The simulation results and experimental results show that the optimal parameter combination of ACO obtained by the UD method can rank in the top 10% of the valid results of the enumeration method sorted by the path length. In addition, the algorithm running time of the optimal parameter combination is shorter than that of most parameter combinations obtained by enumeration method.

KW - ant colony optimization

KW - parameter tuning

KW - path planning

KW - uniform design

UR - https://www.scopus.com/pages/publications/85141346800

U2 - 10.1109/AEECA55500.2022.9918906

DO - 10.1109/AEECA55500.2022.9918906

M3 - 会议稿件

AN - SCOPUS:85141346800

T3 - 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022

SP - 1183

EP - 1191

BT - 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022

Y2 - 20 August 2022 through 21 August 2022

ER -

Yao X, Shi X, Zhang X, Mei X. An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots. In 2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 1183-1191. (2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2022). doi: 10.1109/AEECA55500.2022.9918906

An Ant Colony Optimization Parameter Tuning Method Based on Uniform Design for Path Planning of Mobile Robots

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this