Application and prospect of deep-sea ARV in mineral resource investigation

ZHOU Jixiang; LIU Huimin; LU Kai; SHAN Rui; YANG Yuan

doi:10.16028/j.1009-2722.2023.005

2024 Vol. 40, No. 2

Article Contents

Article navigation > Marine Geology Frontiers > 2024 > 40(2): 93-102

Next Article Previous Article

ZHOU Jixiang, LIU Huimin, LU Kai, SHAN Rui, YANG Yuan. Application and prospect of deep-sea ARV in mineral resource investigation[J]. Marine Geology Frontiers, 2024, 40(2): 93-102. doi: 10.16028/j.1009-2722.2023.005

Citation:

ZHOU Jixiang, LIU Huimin, LU Kai, SHAN Rui, YANG Yuan. Application and prospect of deep-sea ARV in mineral resource investigation[J]. Marine Geology Frontiers, 2024, 40(2): 93-102. doi: 10.16028/j.1009-2722.2023.005

Application and prospect of deep-sea ARV in mineral resource investigation

1.
Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266237, China

More Information

Corresponding author: LIU Huimin, liuhuimin@mail.cgs.gov.cn

Received Date: 06 January 2023

Publish Date: 28 February 2024

Abstract

Abstract

Deep-sea autonomous/remote-operated underwater vehicle (ARV) as an emerging hybrid underwater device, it combines the advantages of the flexibility of autonomous underwater vehicle (AUV) and the human-computer interaction of remotely operated vehicle (ROV), promoting a new model of hybrid autonomous and remote-controlled operations. The deep-sea ARV can be switched to AUV autonomous navigation mode to independently collect data of near-seabed topography, geological structure, and environmental parameters of the surrounding area. It can also be switched to ROV mode for local observation and sampling, depending on the target area of interest, showing future development direction of third-generation deep-sea underwater vehicles with complex mission execution capabilities. The development status of hybrid deep-sea ARV at home and abroad is reviewed. Aiming at deep-sea mineral resources investigation in China, the research and development of the 6 000-m Wenhai 1 ARV system is introduced, along with its key technology and technical challenges, and its main application cases and achievements. At last, some ideas and suggestions on future application scenarios, functional integration, and development directions for deep-sea ARV are presented.
- autonomous/remote operated underwater vehicle /
- AUV autonomous navigation /
- ROV remote control /
- deep sea mineral resources survey /
- "Wenhai 1" ARV system

FullText(HTML)

References

[1]	封锡盛,李一平,徐会希,等. 深海自主水下机器人发展及其在资源调查中的应用[J]. 中国有色金属学报,2021,31(10):2746-2756. Google Scholar
[2]	吴有生,赵羿羽,郎舒妍,等. 智能无人潜水器技术发展研究[J]. 中国工程科学,2020,22(6):26-31. Google Scholar
[3]	李硕,唐元贵,黄琰,等. 深海技术装备研制现状与展望[J]. 中国科学院院刊,2016,31(12):1316-1325. doi: 10.16418/j.issn.1000-3045.2016.12.005 CrossRef Google Scholar
[4]	任玉刚,刘保华,丁忠军,等. 载人潜水器发展现状及趋势[J]. 海洋技术学报,2018,37(2):114-122. Google Scholar
[5]	徐伟哲,张庆勇. 全海深潜水器的技术现状和发展综述[J]. 中国造船,2016,57(2):206-221. doi: 10.3969/j.issn.1000-4882.2016.02.023 CrossRef Google Scholar
[6]	陈宗恒,田烈余,胡波,等. “海马”号ROV在天然气水合物勘查中的应用[J]. 海洋技术学报,2018,37(2):24-29. Google Scholar
[7]	沈克,严允,晏红文. 我国深海作业级ROV技术现状及发展展望[J]. 控制与信息技术,2020,3:1-7. Google Scholar
[8]	李硕,刘健,徐会希,等. 我国深海自主水下机器人的研究现状[J]. 中国科学:信息科学,2018,48(9):1152-1164. Google Scholar
[9]	王振杰,刘慧敏,杨慧良,等. 基于垂直约束的深海拖曳系统USBL/DVL组合导航算法[J]. 中国惯性技术学报,2019,27(5):670-676. doi: 10.13695/j.cnki.12-1222/o3.2019.05.016 CrossRef Google Scholar
[10]	YU C Y,XIANG X B,MAURELLI F,et al. Onboard system of hybrid underwater robotic vehicles:integrated software architecture and control algorithm[J]. Ocean Engineering,2019,187:106121. doi: 10.1016/j.oceaneng.2019.106121 CrossRef Google Scholar
[11]	WANG B,WU C,GE T. Self-repairing control system for a hybrid underwater vehicle[J]. Advanced Materials Research,2014,834/836:1256-1262. Google Scholar
[12]	徐鹏飞. 11 000米ARV总体设计与关键技术研究[D]. 北京: 中国舰船研究院, 2014. Google Scholar
[13]	陆洋,唐元贵,王健,等. 全海深ARV浮力配平计算方法[J]. 机器人,2021,43(1):74-80. doi: 10.13973/j.cnki.robot.200037 CrossRef Google Scholar
[14]	杨新平. 遥控自治水下机器人控制技术研究[D]. 北京: 中国舰船研究院, 2012. Google Scholar
[15]	XIANG X B,ZUO M J,LAPIERRE L,et al. Hybrid underwater robotic vehicles:the state-of-the-art and future trends[J]. Hkie Transactions,2015,22(2):103-116. doi: 10.1080/1023697X.2015.1038322 CrossRef Google Scholar
[16]	王磊,刘涛,杨申申,等. 深海潜水器ARV关键技术[J]. 火力与指挥控制,2010,35(11):6-8. doi: 10.3969/j.issn.1002-0640.2010.11.002 CrossRef Google Scholar
[17]	李一平,李硕,张艾群. 自主/遥控水下机器人研究现状[J]. 工程研究-跨学科视野中的工程,2016,8(2):217-222. Google Scholar
[18]	MOMMA H, WATANABE M, HASHIMOTO K, et al. Loss of the full ocean depth ROV Kaiko-part 1: ROV Kaiko-a review[C]//The Fourteenth International Offshore and Polar Engineering Conference, Yokosuka: International Society of Offshore and Polar Engineers, 2004. Google Scholar
[19]	BOWEN A D,YOERGER D R,TAYLOR C,et al. The Nereus hybrid underwater robotic vehicle[J]. Underwater Technology,2009,28(3):79-89. doi: 10.3723/ut.28.079 CrossRef Google Scholar
[20]	李硕,曾俊宝,王越超. 自治/遥控水下机器人北极冰下导航[J]. 机器人,2011,33(4):509-512. Google Scholar
[21]	唐元贵,王健,陆洋,等. “海斗号”全海深自主遥控水下机器人参数化设计方法与试验研究[J]. 机器人,2019,41(6):697-705. doi: 10.13973/j.cnki.robot.180684 CrossRef Google Scholar
[22]	吴立新,荆钊,陈显尧,等. 我国海洋科学发展现状与未来展望[J]. 地学前缘,2022,29(5):1-12. doi: 10.13745/j.esf.sf.2022.4.60 CrossRef Google Scholar
[23]	吴立新,陈朝晖,林霄沛,等. “透明海洋”立体观测网构建[J]. 科学通报,2020,65(25):2654-2661. Google Scholar
[24]	LI J,JUN B,LEE P,et al. A Hierarchical real-time control architecture for a semi-autonomous underwater vehicle[J]. Ocean Engineering,2005,32(13):1631-1641. doi: 10.1016/j.oceaneng.2004.12.003 CrossRef Google Scholar
[25]	CUI W C,WANG F,PAN B B,et al. Issues to be solved in the design,manufacture and maintenance of full ocean depth manned cabin[J]. Advances in Chemical Engineering and Science,2016,11:1-29. Google Scholar
[26]	SAHOO A,DWIVEDY S K,ROBI P S. Advancements in the field of autonomous underwater vehicle[J]. Ocean Engineering,2019,181:145-160. doi: 10.1016/j.oceaneng.2019.04.011 CrossRef Google Scholar
[27]	FERREIRA C Z,CARDOSO R,MEZA M,et al. Controlling tracking trajectory of a robotic vehicle for inspection of underwater structures[J]. Ocean Engineering,2018,149(2):373-382. Google Scholar
[28]	孙大军,郑翠娥,张居成,等. 水声定位导航技术的发展与展望[J]. 中国科学院院刊,2019,34(3):331-338. doi: 10.16418/j.issn.1000-3045.2019.03.011 CrossRef Google Scholar
[29]	郑冰,孙骁禾,粟京. 一种水下激光成像的新方法[J]. 中国海洋大学学报(自然科学版),2006,36(1):119-122. Google Scholar
[30]	张鑫. 深海环境及深海沉积物拉曼光谱原位定量探测技术研究[D]. 青岛: 中国海洋大学, 2009. Google Scholar
[31]	王冰,宋永东,杜增丰,等. 水下激光扫描成像系统及其在冷泉研究中的应用[J]. 海洋地质前沿,2019,35(11):60-65. doi: 10.16028/j.1009-2722.2019.11009 CrossRef Google Scholar
[32]	潘国伟,曹聚亮,吴美平,等. 水下重力测量技术进展[J]. 测绘通报,2019,2:1-5. doi: 10.13474/j.cnki.11-2246.2019.0033 CrossRef Google Scholar