Overview of Key Technologies for Water-based Automatic Security Marking Platform
Source: By:Aijuan Li, Chunpeng Gong, Xin Huang, Xinnian Sun, Gang Liu
DOI: https://doi.org/10.30564/ese.v4i1.4710
Abstract: Water-based automatic security marking platform composed of multifunctional underwater robots and unmanned surface vessel has become the development trend and focus for exploring complex and dangerous waters,and its related technologies have flourished and gradually developed from single control to multi-platform collaborative direction in complex and dangerous waters to reduce casualties. This paper composes and analyzes the key technologies of the water-based automatic security marking platform based on the cable underwater robot and the unmanned surface vessel, describes the research and application status of the key technologies of the water-based automatic security marking platform from the aspects of the unmanned surface vessel, underwater robot and underwater multisensor information fusion, and outlooks the research direction and focus of the water automatic security inspection and marking platform. References:[1] Chen, D.J., 2020. Research on the status of application of police robots in Zhejiang public security. Light Industry Science and Technology. 36(05), 69-71. [2] Hui, X.U, Jiang, C., 2021. Heterogeneous oceanographic exploration system based on USV and AUV: A survey of developments and challenges. [3] German, C.R., Jakuba, M.V., Kinsey, J.C., et al.,2012. A long term vision for long-range ship-free deep ocean operations: Persistent presence through coordination of autonomous surface vehicles and autonomous underwater vehicles. 2012 IEEE/OES Autonomous Underwater Vehicles (AUV). IEEE. pp. 1-7. [4] Liu, Y., Liu, W., Song, R., et al., 2017. Predictive navigation of unmanned surface vehicles in a dynamic maritime environment when using the fast marching method. International Journal of Adaptive Control and Signal Processing. 31(4), 464-488. [5] Shao, G., Ma, Y., Malekian, R., et al., 2019. A novel cooperative platform design for coupled USV–UAV systems. IEEE Transactions on Industrial Informatics. 15(9), 4913-4922. [6] Nava-Balanzar, L., Sánchez-Gaytán, J.L., Fonseca-Navarro, F., et al., 2017. Towards Teleoperation and Automatic Control Features of an Unmanned Surface Vessel-ROV System: Preliminary Results. ICINCO (2). pp. 292-299. [7] Lee, J., Jin, H.S., Cho, H., et al., 2020. A New Complex Marine Unmanned Platform and Field Test. Journal of Marine Science and Technology. 28(6), 9. [8] Lachaud, E., Monbeig, Y., Nolleau, P., et al., 2018. Opportunities and Challenges of Remote Operating a ROV Embarked on a USV. Offshore Technology Conference. OnePetro. [9] Quan, W., Liu, Y., Zhang, A., et al., 2016. The nonlinear finite element modeling and performance analysis of the passive heave compensation system for the deep-sea tethered ROVs. Ocean Engineering. 127, 246-257. [10] Chen, Z.H., Sheng, Y., Tao, J., 2009. A review on the structure of remotely operated underwater robots-Example of HYSUB130-4000 ROV system. Marine Geology. 3, 64-71. [11] Liu, Q., Tan, Y.X., 1999. Research on the difference between single and catamaran taxi boats and the scope of application of catamaran taxi boats. Jiangsu Ship. (02), 33-36+44. [12] Wu, J., Wang, Z.D., Ling, H.J., et al., 2020. Review of key technologies for deep-sea operational underwater robots with cables. Journal of Jiangsu University of Science and Technology (Natural Science Edition). 34(04), 1-12. [13] Barrera, C., Padron, I., Luis, F.S., et al., 2021. Trends and challenges in unmanned surface vehicles (Usv): From survey to shipping. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation. 15. [14] Corfield, S., Young, J., 2006. Unmanned surface vehicles-game changing technology for naval operations. IEEE Control Engineering Series. 69, 311. [15] Tang, H.B., 2020. Research status and development trend of surface unmanned boats. Ship Materials and Markets. (03), 13-14. [16] He, P., Yang, M., Ma, Y., 2012. Global naval warfare robot. Beijing PLA Press. [17] Liu, J.P., 2019. Unveiling the prologue of unmanned naval warfare, China’s “Lookout” II unmanned boat. Tank Armored Vehicle. (02), 26-30. [18] Moud, H.I., Shojaei, A., Flood, I., 2018. Current and future applications of unmanned surface, underwater, and ground vehicles in construction. Proceedings of the Construction Research Congress. pp. 106-115. [19] Jorge, V.A.M., Granada, R., Maidana, R.G., et al., 2019. A survey on unmanned surface vehicles for disaster robotics: Main challenges and directions.Sensors. 19(3), 702. [20] Sager, W.W., Shyu, J.P., Manley, J., 2008. Exploring West Florida Escarpment with High-Resolution Geophysical Imaging. UNE. 1, 11. [21] Peng, Y., Luo, A.X., 2015. The battle at sea-A chronicle of Shanghai University’s Jinghai unmanned boat series development. China Military to Civilian. (02), 37-39. [22] Hine, R., McGillivary, P., 2007. Wave powered autonomous surface vessels as components of ocean observing systems. Proceeding of PACON. pp. 1-9. [23] Song, Zh.W., 2016. Underwater structure inspection and operation robot ROV development and sonar image recognition research. Jiangsu University of Science and Technology. [24] Peng, Y., Yang, Y., Cui, J., et al., 2017. Development of the USV “JingHai-I” and sea trials in the Southern Yellow Sea. Ocean Engineering. 131, 186-196. [25] Wang, Y.D., Wang, P., Sun, P.F., 2021. A review of autonomous underwater robot control technology. World Science and Technology Research and Development. 43(6), 636. [26] Feng, Zh.P., 2005. Review of the development status of foreign autonomous underwater robots. Torpedo Technology. (01), 5-9. [27] Wynn, R.B., Huvenne, V.A.I., Le Bas, T.P., et al., 2014. Autonomous Underwater Vehicles (AUVs): Their past, present and future contributions to the advancement of marine geoscience. Marine Geology. 352, 451-468. [28] Yu, M.G., Zhang, X., Chen, Z.H., 2017. A review of autonomous underwater robotics. Mechatronics Engineering Technology. 46(08), 155-157. [29] Alt, C.V., 2003. REMUS 100 Transportable Mine Countermeasure Package. Oceans. IEEE, Proceedings, San Diego, California, USA. [30] Jaffre, F., Littlefield, R., Grund, M., et al., 2019. Development of a new version of the remus 6000 autonomous underwater vehicle. OCEANS 2019-Marseille. IEEE. pp. 1-7. [31] Li, D., Ji, D., Liu, J., et al., 2016. A multi-model EKF integrated navigation algorithm for deep water AUV. International Journal of Advanced Robotic Systems. 13(1), 3. [32] “Wukong” sets a new record for AUV dive depth in China. Sensor World. 2021. 27(04), 31. [33] Cui, W., 2018. An overview of submersible research and development in China. Journal of Marine Science and Application. 17(4), 459-470. [34] Cao, X., Sun, H., Jan, G.E., 2018. Multi-AUV cooperative target search and tracking in unknown underwater environment. Ocean Engineering. 150, 1-11. [35] Kim, K., Tamura, K., 2016. The Zipangu of the Sea project overview: focusing on the R&D for simultaneous deployment and operation of multiple AUVs. Offshore Technology Conference Asia. OnePetro. [36] Tarwadi, P., Shiraki, Y., Ganoni, O., et al., 2020. Design and Development of a Robotic Vehicle for Shallow-Water Marine Inspections. arXiv preprint arXiv:2007.04563. [37] Nicolas, T., Vincent, M., Steven, L.B., 2020. Innovative Use of a Rov to Control Underwater Coastal Protections. Offshore Technology Conference.OnePetro. [38] Xia, P., McSweeney, K., Wen, F., et al., 2022. Virtual Telepresence for the Future of ROV Teleoperations: Opportunities and Challenges. SNAME 27th Off-shore Symposium. OnePetro. [39] He, Y., Wang, D.B., Ali, Z.A., 2020. A review of different designs and control models of remotely operated underwater vehicle. Measurement and Control. 53(9-10), 1561-1570. [40] Aras, M.S.M., Abdullah, S.S., Azis, F.A., 2015. Review on auto-depth control system for an unmanned underwater remotely operated vehicle (ROV) using intelligent controller. Journal of Telecommunication, Electronic and Computer Engineering (JTEC). 7(1), 47-55. [41] Chen, Z.H., Sheng, Y., Hu, B., 2014. The development status and application of ROV in marine scientific research. Science and Technology Innovation and Application. (21), 3-4. [42] Xia, Q.S., Liu, Y.H., 2013. Research status and prospect of underwater target fusion identification technology. Torpedo Technology. 21(03), 234-240. [43] Guan, M., Cheng, Y., Li, Q., et al., 2019. An effective method for submarine buried pipeline detection via multi-sensor data fusion. IEEE Access. 7, 125300-125309. [44] Rahman, S., 2020. A Multi-Sensor Fusion-Based Underwater Slam System. University of South Carolina. [45] Xing, H., Liu, Y., Guo, S., et al., 2021. A Multi-Sensor Fusion Self-Localization System of a Miniature Underwater Robot in Structured and GPS-Denied Environments. IEEE Sensors Journal. 21(23), 27136-27146. [46] Wu, Y., Ta, X., Xiao, R., et al., 2019. Survey of underwater robot positioning navigation. Applied Ocean Research. 90, 101845. [47] Guleria, K., Atham, S.B., Kumar, A., 2021. Data Fusion in Underwater Wireless Sensor Networks and Open Research Challenges. Energy-Efficient Underwater Wireless Communications and Networking. IGI Global. pp. 67-84. [48] Balckman, S.S., 1990. Association and fusion of multiple sensor data. Chapter 6: in multitarget-multisensor tracking: advanced applications. [49] Liu, Y., 2020. Research on multi-sensor-based vehicle environment sensing technology. Changchun University of Science and Technology. [50] Li, C., Zhu, G., 2019. Underwater multi-sensor Bayesian distributed detection and data fusion. MATEC Web of Conferences. EDP Sciences. 283, 07014. [51] Shao, Z.Zh., 2013. Multi-sensor data fusion in hydroacoustic signal processing. China Science and Technology Information. (09), 63.