Unmanned aerial vehicle route planning method based on a star algorithm

Tianyou Chen; Guofeng Zhang; Xiaoguang Hu; Jin Xiao

doi:10.1109/ICIEA.2018.8397948

Unmanned aerial vehicle route planning method based on a star algorithm

Tianyou Chen
, Guofeng Zhang
, Xiaoguang Hu
, Jin Xiao

School of Automation Science and Electrical Engineering

Beihang University

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

61 Scopus citations

Abstract

On the basis of studying and analyzing the basic principles of A star algorithm, this paper compares its advantages and disadvantages with those of genetic algorithm and ant colony algorithm. In the meantime, the paper builds the model of unmanned aerial vehicle(UAV) battlefield environment for route planning and applies the A star algorithm to UAV route planning under the constraints of bearing the least danger and consuming the least fuel. Finally, the paper uses python programming language to simulate the UAV route planning, whose result shows the validity of the model and the feasibility of the algorithm.

Original language	English
Title of host publication	Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1510-1514
Number of pages	5
ISBN (Electronic)	9781538637579
DOIs	https://doi.org/10.1109/ICIEA.2018.8397948
State	Published - 26 Jun 2018
Event	13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018 - Wuhan, China Duration: 31 May 2018 → 2 Jun 2018

Publication series

Name	Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

Conference

Conference	13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018
Country/Territory	China
City	Wuhan
Period	31/05/18 → 2/06/18

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

A algorithm
route planning
unmanned aerial vehicle

Access to Document

10.1109/ICIEA.2018.8397948

Cite this

Chen, T., Zhang, G., Hu, X., & Xiao, J. (2018). Unmanned aerial vehicle route planning method based on a star algorithm. In Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018 (pp. 1510-1514). (Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA.2018.8397948

Chen, Tianyou ; Zhang, Guofeng ; Hu, Xiaoguang et al. / Unmanned aerial vehicle route planning method based on a star algorithm. Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1510-1514 (Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018).

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title = "Unmanned aerial vehicle route planning method based on a star algorithm",

abstract = "On the basis of studying and analyzing the basic principles of A star algorithm, this paper compares its advantages and disadvantages with those of genetic algorithm and ant colony algorithm. In the meantime, the paper builds the model of unmanned aerial vehicle(UAV) battlefield environment for route planning and applies the A star algorithm to UAV route planning under the constraints of bearing the least danger and consuming the least fuel. Finally, the paper uses python programming language to simulate the UAV route planning, whose result shows the validity of the model and the feasibility of the algorithm.",

keywords = "A algorithm, route planning, unmanned aerial vehicle",

author = "Tianyou Chen and Guofeng Zhang and Xiaoguang Hu and Jin Xiao",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018 ; Conference date: 31-05-2018 Through 02-06-2018",

year = "2018",

month = jun,

day = "26",

doi = "10.1109/ICIEA.2018.8397948",

language = "英语",

series = "Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018",

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

pages = "1510--1514",

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address = "美国",

}

Chen, T, Zhang, G, Hu, X & Xiao, J 2018, Unmanned aerial vehicle route planning method based on a star algorithm. in Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018. Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1510-1514, 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018, Wuhan, China, 31/05/18. https://doi.org/10.1109/ICIEA.2018.8397948

Unmanned aerial vehicle route planning method based on a star algorithm. / Chen, Tianyou; Zhang, Guofeng; Hu, Xiaoguang et al.
Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1510-1514 (Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018).

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

TY - GEN

T1 - Unmanned aerial vehicle route planning method based on a star algorithm

AU - Chen, Tianyou

AU - Zhang, Guofeng

AU - Hu, Xiaoguang

AU - Xiao, Jin

PY - 2018/6/26

Y1 - 2018/6/26

N2 - On the basis of studying and analyzing the basic principles of A star algorithm, this paper compares its advantages and disadvantages with those of genetic algorithm and ant colony algorithm. In the meantime, the paper builds the model of unmanned aerial vehicle(UAV) battlefield environment for route planning and applies the A star algorithm to UAV route planning under the constraints of bearing the least danger and consuming the least fuel. Finally, the paper uses python programming language to simulate the UAV route planning, whose result shows the validity of the model and the feasibility of the algorithm.

AB - On the basis of studying and analyzing the basic principles of A star algorithm, this paper compares its advantages and disadvantages with those of genetic algorithm and ant colony algorithm. In the meantime, the paper builds the model of unmanned aerial vehicle(UAV) battlefield environment for route planning and applies the A star algorithm to UAV route planning under the constraints of bearing the least danger and consuming the least fuel. Finally, the paper uses python programming language to simulate the UAV route planning, whose result shows the validity of the model and the feasibility of the algorithm.

KW - A algorithm

KW - route planning

KW - unmanned aerial vehicle

UR - https://www.scopus.com/pages/publications/85050131974

U2 - 10.1109/ICIEA.2018.8397948

DO - 10.1109/ICIEA.2018.8397948

M3 - 会议稿件

AN - SCOPUS:85050131974

T3 - Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

SP - 1510

EP - 1514

BT - Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

Y2 - 31 May 2018 through 2 June 2018

ER -

Chen T, Zhang G, Hu X , Xiao J. Unmanned aerial vehicle route planning method based on a star algorithm. In Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1510-1514. (Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018). doi: 10.1109/ICIEA.2018.8397948

Unmanned aerial vehicle route planning method based on a star algorithm

Abstract

Publication series

Conference

UN SDGs

Keywords

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