Multi-UUV/USV Adaptive Cooperative Search Using Online State Information

Wenjie Li; Jian Gao; Yimin Chen; Pei Cui; Junjun Lv; Guang Pan

doi:10.1007/978-981-99-6498-7_24

Multi-UUV/USV Adaptive Cooperative Search Using Online State Information

Wenjie Li, Jian Gao, Yimin Chen, Pei Cui, Junjun Lv, Guang Pan

School of Marine Science and Technology

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

2 Scopus citations

Abstract

Unmanned Surface Vessel (USV) and Unmanned Underwater Vehicle (UUV) detect the same task plane while located in different planes, and have to avoid obstacles autonomously in cooperative search in unknown environments. This paper proposes an adaptive cooperative search method for a USV/UUV heterogeneous cross-domain swarm based on online state information. Considering the different planes of USV/UUV detection, we establish a USV/UUV detection model with a forward-looking sonar according to the cross-sectional view. In order to guarantee the safety of USV/UUV, an obstacle avoidance algorithm based on predictive guidance is designed. Finally, the task environment is rasterized to establish the state information structure of grids and USV/UUV. On this basis, USV/UUV adaptively plans the search path according to its own motion state. The state information of each grid is updated online until USV/UUV swarm completes the search task. Simulation results show that USV/UUV can accomplish cooperative search safely in an unknown environment. Compared with a UUV homogeneous swarm, the USV/UUV swarm shortens the search time and improves the cooperative search efficiency.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings
Editors	Huayong Yang, Jun Zou, Geng Yang, Xiaoping Ouyang, Honghai Liu, Zhouping Yin, Lianqing Liu, Zhiyong Wang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	269-280
Number of pages	12
ISBN (Print)	9789819964970
DOIs	https://doi.org/10.1007/978-981-99-6498-7_24
State	Published - 2023
Event	16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 - Hangzhou, China Duration: 5 Jul 2023 → 7 Jul 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14273 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Intelligent Robotics and Applications, ICIRA 2023
Country/Territory	China
City	Hangzhou
Period	5/07/23 → 7/07/23

Keywords

Cooperative search
Detection model
Heterogeneous swarm
USV/UUV

Access to Document

10.1007/978-981-99-6498-7_24

Cite this

Li, W., Gao, J., Chen, Y., Cui, P., Lv, J., & Pan, G. (2023). Multi-UUV/USV Adaptive Cooperative Search Using Online State Information. In H. Yang, J. Zou, G. Yang, X. Ouyang, H. Liu, Z. Yin, L. Liu, & Z. Wang (Eds.), Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings (pp. 269-280). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14273 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-6498-7_24

Li, Wenjie ; Gao, Jian ; Chen, Yimin et al. / Multi-UUV/USV Adaptive Cooperative Search Using Online State Information. Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. editor / Huayong Yang ; Jun Zou ; Geng Yang ; Xiaoping Ouyang ; Honghai Liu ; Zhouping Yin ; Lianqing Liu ; Zhiyong Wang. Springer Science and Business Media Deutschland GmbH, 2023. pp. 269-280 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{faaf2eb0ae244cb8b76a4b19762d3001,

title = "Multi-UUV/USV Adaptive Cooperative Search Using Online State Information",

abstract = "Unmanned Surface Vessel (USV) and Unmanned Underwater Vehicle (UUV) detect the same task plane while located in different planes, and have to avoid obstacles autonomously in cooperative search in unknown environments. This paper proposes an adaptive cooperative search method for a USV/UUV heterogeneous cross-domain swarm based on online state information. Considering the different planes of USV/UUV detection, we establish a USV/UUV detection model with a forward-looking sonar according to the cross-sectional view. In order to guarantee the safety of USV/UUV, an obstacle avoidance algorithm based on predictive guidance is designed. Finally, the task environment is rasterized to establish the state information structure of grids and USV/UUV. On this basis, USV/UUV adaptively plans the search path according to its own motion state. The state information of each grid is updated online until USV/UUV swarm completes the search task. Simulation results show that USV/UUV can accomplish cooperative search safely in an unknown environment. Compared with a UUV homogeneous swarm, the USV/UUV swarm shortens the search time and improves the cooperative search efficiency.",

keywords = "Cooperative search, Detection model, Heterogeneous swarm, USV/UUV",

author = "Wenjie Li and Jian Gao and Yimin Chen and Pei Cui and Junjun Lv and Guang Pan",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.; 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 ; Conference date: 05-07-2023 Through 07-07-2023",

year = "2023",

doi = "10.1007/978-981-99-6498-7_24",

language = "英语",

isbn = "9789819964970",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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

pages = "269--280",

editor = "Huayong Yang and Jun Zou and Geng Yang and Xiaoping Ouyang and Honghai Liu and Zhouping Yin and Lianqing Liu and Zhiyong Wang",

booktitle = "Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings",

}

Li, W, Gao, J, Chen, Y, Cui, P, Lv, J & Pan, G 2023, Multi-UUV/USV Adaptive Cooperative Search Using Online State Information. in H Yang, J Zou, G Yang, X Ouyang, H Liu, Z Yin, L Liu & Z Wang (eds), Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14273 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 269-280, 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, Hangzhou, China, 5/07/23. https://doi.org/10.1007/978-981-99-6498-7_24

Multi-UUV/USV Adaptive Cooperative Search Using Online State Information. / Li, Wenjie; Gao, Jian; Chen, Yimin et al.
Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. ed. / Huayong Yang; Jun Zou; Geng Yang; Xiaoping Ouyang; Honghai Liu; Zhouping Yin; Lianqing Liu; Zhiyong Wang. Springer Science and Business Media Deutschland GmbH, 2023. p. 269-280 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14273 LNAI).

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

TY - GEN

T1 - Multi-UUV/USV Adaptive Cooperative Search Using Online State Information

AU - Li, Wenjie

AU - Gao, Jian

AU - Chen, Yimin

AU - Cui, Pei

AU - Lv, Junjun

AU - Pan, Guang

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

PY - 2023

Y1 - 2023

N2 - Unmanned Surface Vessel (USV) and Unmanned Underwater Vehicle (UUV) detect the same task plane while located in different planes, and have to avoid obstacles autonomously in cooperative search in unknown environments. This paper proposes an adaptive cooperative search method for a USV/UUV heterogeneous cross-domain swarm based on online state information. Considering the different planes of USV/UUV detection, we establish a USV/UUV detection model with a forward-looking sonar according to the cross-sectional view. In order to guarantee the safety of USV/UUV, an obstacle avoidance algorithm based on predictive guidance is designed. Finally, the task environment is rasterized to establish the state information structure of grids and USV/UUV. On this basis, USV/UUV adaptively plans the search path according to its own motion state. The state information of each grid is updated online until USV/UUV swarm completes the search task. Simulation results show that USV/UUV can accomplish cooperative search safely in an unknown environment. Compared with a UUV homogeneous swarm, the USV/UUV swarm shortens the search time and improves the cooperative search efficiency.

AB - Unmanned Surface Vessel (USV) and Unmanned Underwater Vehicle (UUV) detect the same task plane while located in different planes, and have to avoid obstacles autonomously in cooperative search in unknown environments. This paper proposes an adaptive cooperative search method for a USV/UUV heterogeneous cross-domain swarm based on online state information. Considering the different planes of USV/UUV detection, we establish a USV/UUV detection model with a forward-looking sonar according to the cross-sectional view. In order to guarantee the safety of USV/UUV, an obstacle avoidance algorithm based on predictive guidance is designed. Finally, the task environment is rasterized to establish the state information structure of grids and USV/UUV. On this basis, USV/UUV adaptively plans the search path according to its own motion state. The state information of each grid is updated online until USV/UUV swarm completes the search task. Simulation results show that USV/UUV can accomplish cooperative search safely in an unknown environment. Compared with a UUV homogeneous swarm, the USV/UUV swarm shortens the search time and improves the cooperative search efficiency.

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Li W, Gao J, Chen Y, Cui P, Lv J, Pan G. Multi-UUV/USV Adaptive Cooperative Search Using Online State Information. In Yang H, Zou J, Yang G, Ouyang X, Liu H, Yin Z, Liu L, Wang Z, editors, Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 269-280. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-981-99-6498-7_24

Multi-UUV/USV Adaptive Cooperative Search Using Online State Information

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