Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones

Xinyi Li; Kewei Xia

doi:10.1007/978-981-97-3336-1_48

Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones

Xinyi Li, Kewei Xia^*

^*Corresponding author for this work

Advanced Research Institute of Multidisciplinary Science

Beijing Institute of Technology

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

Abstract

This paper investigates the trajectory planning and target tracking of multiple unmanned aerial vehicles (UAVs) in the presence of static obstacles. Specifically, a composite strategy that exploits the action mechanism of multiple virtual pheromones in the environment is proposed, where the static obstacles, target and UAVs are characterized by the repulsive, attractive and traceable pheromones, respectively. Based on the responses to the described virtual pheromones simultaneously, the trajectory planning and target tracking can be achieved for each UAV. Simulation examples are provided to validate the proposed strategy.

Original language	English
Title of host publication	Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies
Editors	Xiaoduo Li, Xun Song, Yingjiang Zhou
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	563-571
Number of pages	9
ISBN (Print)	9789819733354
DOIs	https://doi.org/10.1007/978-981-97-3336-1_48
Publication status	Published - 2024
Event	7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023 - Nanjing, China Duration: 24 Nov 2023 → 27 Nov 2023

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1207 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023
Country/Territory	China
City	Nanjing
Period	24/11/23 → 27/11/23

Keywords

multiple virtual pheromone
target tracking
trajectory planning
unmanned aerial vehicles

Access to Document

10.1007/978-981-97-3336-1_48

Cite this

Li, X., & Xia, K. (2024). Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones. In X. Li, X. Song, & Y. Zhou (Eds.), Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies (pp. 563-571). (Lecture Notes in Electrical Engineering; Vol. 1207 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-3336-1_48

Li, Xinyi ; Xia, Kewei. / Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones. Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies. editor / Xiaoduo Li ; Xun Song ; Yingjiang Zhou. Springer Science and Business Media Deutschland GmbH, 2024. pp. 563-571 (Lecture Notes in Electrical Engineering).

@inproceedings{94cda7010865476baed880a97886b86b,

title = "Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones",

abstract = "This paper investigates the trajectory planning and target tracking of multiple unmanned aerial vehicles (UAVs) in the presence of static obstacles. Specifically, a composite strategy that exploits the action mechanism of multiple virtual pheromones in the environment is proposed, where the static obstacles, target and UAVs are characterized by the repulsive, attractive and traceable pheromones, respectively. Based on the responses to the described virtual pheromones simultaneously, the trajectory planning and target tracking can be achieved for each UAV. Simulation examples are provided to validate the proposed strategy.",

keywords = "multiple virtual pheromone, target tracking, trajectory planning, unmanned aerial vehicles",

author = "Xinyi Li and Kewei Xia",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023 ; Conference date: 24-11-2023 Through 27-11-2023",

year = "2024",

doi = "10.1007/978-981-97-3336-1_48",

language = "English",

isbn = "9789819733354",

series = "Lecture Notes in Electrical Engineering",

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

pages = "563--571",

editor = "Xiaoduo Li and Xun Song and Yingjiang Zhou",

booktitle = "Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies",

address = "Germany",

}

Li, X & Xia, K 2024, Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones. in X Li, X Song & Y Zhou (eds), Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies. Lecture Notes in Electrical Engineering, vol. 1207 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 563-571, 7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023, Nanjing, China, 24/11/23. https://doi.org/10.1007/978-981-97-3336-1_48

Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones. / Li, Xinyi; Xia, Kewei.
Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies. ed. / Xiaoduo Li; Xun Song; Yingjiang Zhou. Springer Science and Business Media Deutschland GmbH, 2024. p. 563-571 (Lecture Notes in Electrical Engineering; Vol. 1207 LNEE).

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

TY - GEN

T1 - Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones

AU - Li, Xinyi

AU - Xia, Kewei

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

PY - 2024

Y1 - 2024

N2 - This paper investigates the trajectory planning and target tracking of multiple unmanned aerial vehicles (UAVs) in the presence of static obstacles. Specifically, a composite strategy that exploits the action mechanism of multiple virtual pheromones in the environment is proposed, where the static obstacles, target and UAVs are characterized by the repulsive, attractive and traceable pheromones, respectively. Based on the responses to the described virtual pheromones simultaneously, the trajectory planning and target tracking can be achieved for each UAV. Simulation examples are provided to validate the proposed strategy.

AB - This paper investigates the trajectory planning and target tracking of multiple unmanned aerial vehicles (UAVs) in the presence of static obstacles. Specifically, a composite strategy that exploits the action mechanism of multiple virtual pheromones in the environment is proposed, where the static obstacles, target and UAVs are characterized by the repulsive, attractive and traceable pheromones, respectively. Based on the responses to the described virtual pheromones simultaneously, the trajectory planning and target tracking can be achieved for each UAV. Simulation examples are provided to validate the proposed strategy.

KW - multiple virtual pheromone

KW - target tracking

KW - trajectory planning

KW - unmanned aerial vehicles

UR - http://www.scopus.com/inward/record.url?scp=85199348383&partnerID=8YFLogxK

U2 - 10.1007/978-981-97-3336-1_48

DO - 10.1007/978-981-97-3336-1_48

M3 - Conference contribution

AN - SCOPUS:85199348383

SN - 9789819733354

T3 - Lecture Notes in Electrical Engineering

SP - 563

EP - 571

BT - Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies

A2 - Li, Xiaoduo

A2 - Song, Xun

A2 - Zhou, Yingjiang

PB - Springer Science and Business Media Deutschland GmbH

T2 - 7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

Y2 - 24 November 2023 through 27 November 2023

ER -

Li X, Xia K. Trajectory Planning and Target Tracking of UAVs Using Multiple Virtual Pheromones. In Li X, Song X, Zhou Y, editors, Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Decision and Planning Technologies. Springer Science and Business Media Deutschland GmbH. 2024. p. 563-571. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-97-3336-1_48