A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm

Tianqi Qie; Weida Wang; Chao Yang; Ying Li; Wenjie Liu

doi:10.1007/978-981-99-0479-2_338

A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm

Tianqi Qie^*, Weida Wang, Chao Yang, Ying Li, Wenjie Liu

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

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

Abstract

Autonomous flying vehicles are promising transportation of the future, which have the function of ground vehicles and low-altitude aircraft. To plan a feasible path effectively, an improved optimal rapidly-exploring random tree (RRT*) method is proposed. Firstly, a cost function considering driving efficiency and the energy consumption is established. Then, the cost of a known feasible path, which flies from the start point to the goal point directly, is calculated as a benchmark. According to the benchmark, the planning area is reduced to an elliptical area. The proposed method is verified by simulations with an actual cross-country environment. Results show that the computation time decreased by 11.3% compared with the basic RRT* method.

Original language	English
Title of host publication	Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022
Editors	Wenxing Fu, Mancang Gu, Yifeng Niu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	3665-3675
Number of pages	11
ISBN (Print)	9789819904785
DOIs	https://doi.org/10.1007/978-981-99-0479-2_338
Publication status	Published - 2023
Event	International Conference on Autonomous Unmanned Systems, ICAUS 2022 - Xi'an, China Duration: 23 Sept 2022 → 25 Sept 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1010 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Autonomous Unmanned Systems, ICAUS 2022
Country/Territory	China
City	Xi'an
Period	23/09/22 → 25/09/22

Keywords

Autonomous flying vehicles
Path planning
Rapidly-exploring random tree

UN SDGs

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

Access to Document

10.1007/978-981-99-0479-2_338

Cite this

Qie, T., Wang, W., Yang, C., Li, Y., & Liu, W. (2023). A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm. In W. Fu, M. Gu, & Y. Niu (Eds.), Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022 (pp. 3665-3675). (Lecture Notes in Electrical Engineering; Vol. 1010 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-0479-2_338

Qie, Tianqi ; Wang, Weida ; Yang, Chao et al. / A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm. Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022. editor / Wenxing Fu ; Mancang Gu ; Yifeng Niu. Springer Science and Business Media Deutschland GmbH, 2023. pp. 3665-3675 (Lecture Notes in Electrical Engineering).

@inproceedings{9df037f99dd643f4ad608616eb51cb48,

title = "A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm",

abstract = "Autonomous flying vehicles are promising transportation of the future, which have the function of ground vehicles and low-altitude aircraft. To plan a feasible path effectively, an improved optimal rapidly-exploring random tree (RRT*) method is proposed. Firstly, a cost function considering driving efficiency and the energy consumption is established. Then, the cost of a known feasible path, which flies from the start point to the goal point directly, is calculated as a benchmark. According to the benchmark, the planning area is reduced to an elliptical area. The proposed method is verified by simulations with an actual cross-country environment. Results show that the computation time decreased by 11.3% compared with the basic RRT* method.",

keywords = "Autonomous flying vehicles, Path planning, Rapidly-exploring random tree",

author = "Tianqi Qie and Weida Wang and Chao Yang and Ying Li and Wenjie Liu",

note = "Publisher Copyright: {\textcopyright} 2023, Beijing HIWING Sci. and Tech. Info Inst.; International Conference on Autonomous Unmanned Systems, ICAUS 2022 ; Conference date: 23-09-2022 Through 25-09-2022",

year = "2023",

doi = "10.1007/978-981-99-0479-2_338",

language = "English",

isbn = "9789819904785",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

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editor = "Wenxing Fu and Mancang Gu and Yifeng Niu",

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}

Qie, T, Wang, W , Yang, C , Li, Y & Liu, W 2023, A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm. in W Fu, M Gu & Y Niu (eds), Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022. Lecture Notes in Electrical Engineering, vol. 1010 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 3665-3675, International Conference on Autonomous Unmanned Systems, ICAUS 2022, Xi'an, China, 23/09/22. https://doi.org/10.1007/978-981-99-0479-2_338

A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm. / Qie, Tianqi; Wang, Weida ; Yang, Chao et al.
Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022. ed. / Wenxing Fu; Mancang Gu; Yifeng Niu. Springer Science and Business Media Deutschland GmbH, 2023. p. 3665-3675 (Lecture Notes in Electrical Engineering; Vol. 1010 LNEE).

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

TY - GEN

T1 - A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm

AU - Qie, Tianqi

AU - Wang, Weida

AU - Yang, Chao

AU - Li, Ying

AU - Liu, Wenjie

PY - 2023

Y1 - 2023

N2 - Autonomous flying vehicles are promising transportation of the future, which have the function of ground vehicles and low-altitude aircraft. To plan a feasible path effectively, an improved optimal rapidly-exploring random tree (RRT*) method is proposed. Firstly, a cost function considering driving efficiency and the energy consumption is established. Then, the cost of a known feasible path, which flies from the start point to the goal point directly, is calculated as a benchmark. According to the benchmark, the planning area is reduced to an elliptical area. The proposed method is verified by simulations with an actual cross-country environment. Results show that the computation time decreased by 11.3% compared with the basic RRT* method.

AB - Autonomous flying vehicles are promising transportation of the future, which have the function of ground vehicles and low-altitude aircraft. To plan a feasible path effectively, an improved optimal rapidly-exploring random tree (RRT*) method is proposed. Firstly, a cost function considering driving efficiency and the energy consumption is established. Then, the cost of a known feasible path, which flies from the start point to the goal point directly, is calculated as a benchmark. According to the benchmark, the planning area is reduced to an elliptical area. The proposed method is verified by simulations with an actual cross-country environment. Results show that the computation time decreased by 11.3% compared with the basic RRT* method.

KW - Autonomous flying vehicles

KW - Path planning

KW - Rapidly-exploring random tree

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BT - Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022

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PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Autonomous Unmanned Systems, ICAUS 2022

Y2 - 23 September 2022 through 25 September 2022

ER -

Qie T, Wang W , Yang C , Li Y, Liu W. A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm. In Fu W, Gu M, Niu Y, editors, Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 3665-3675. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-99-0479-2_338

A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm

Abstract

Publication series

Conference

Keywords

UN SDGs

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