基于科学引文索引数据库及相关科技文献数据,分析国外军用无人潜航器技术的研究热点,着重研究无人潜航器技术军事应用重点解决的问题和对未来作战的影响。相关结果初步勾勒国外军用无人潜航器技术发展全貌,可为理清军用无人潜航器技术方向提供参考。
Based on the scientific citation index database and relevant scientific and technological literature data, this article analyzes the research hotspots of foreign military unmanned underwater vehicle technology, focusing on the key problems to be solved in military applications of unmanned underwater vehicle technology and its impact on future operations. The relevant results provide a preliminary overview of the development of military unmanned underwater vehicle technology abroad, which can provide reference for clarifying the direction of military unmanned underwater vehicle technology.
2024,46(4): 185-189 收稿日期:2023-08-14
DOI:10.3404/j.issn.1672-7649.2024.04.035
分类号:U661
作者简介:张大中(1996-),男,硕士,助理工程师,研究方向为无人系统
参考文献:
[1] JOSEPH R E. Data-driven learning and modeling of AUV operational characteristics for optimal path planning[J]. Oceans, 2017: 75-53.
[2] COCOCCIONI MARCO. Game theory for unmanned vehicle path planning in the marine domain: state of the art and new possibilities[J]. Journal of Marine Science and Engineering, 2021, 9(11): 1175-1177.
[3] CHARIS N. A comparative study on Ant Colony Optimization algorithm approaches for solving multi-objective path planning problems in case of unmanned surface vehicles[J]. Ocean Engineering, 2022, 255.
[4] PARK J. Mission planning and performance verification of an unmanned surface vehicle using a genetic algorithm[J]. International Journal of Naval Architecture and Ocean Engineering, 2020, 13.
[5] BEN Y. Detection of unanticipated faults for autonomous underwater vehicles using online topic models[J]. J Field Robotics, 2018, 35: 705–716.
[6] RICCARDO C. Interoperability among unmanned maritime vehicles: review and first in-field experimentation[J]. Frontiers in Robotics and AI, 2020, 791.
[7] GLORIA C. Human-autonomy teaming interface design considerations for multi-unmanned vehicle control[J]. Theoretical Issues in Ergonomics Science, 2018 19(3): 321-352.
[8] PEDRO M L. Monitor and control human-computer interface for unmanned surface vehicle fleets[J]. Oceans, 2019, 1-5.
[9] JONATHAN A. Modeling the human visuo-motor system to support remote-control operation[J]. Sensors (Basel), 2019, 18(9): 2979.
[10] SIERRA N Y. Review of human-machine interfaces for small unmanned systems with robotic manipulators[J]. Transactions on Human-machine Systems, 2020, 50(2): 131-143.
[11] OSLER S. Controlling remotely operated vehicles with deterministic artificial intelligence[J]. Applied Sciences, 2022, 12(6): 2810.
[12] JAN S. Bandwidth efficient concurrent localisation and communication in underwater acoustic networks[J]. Kobe Techno-Ocean, 2018, 1-7.
[13] GABRIELE F. localisation through next generation underwater acoustic networks: results from the field[J]. IROS, 2016, 1328-1333.
[14] RIDGE J, NELSON C, WALKER O, et al. Underwater 2-D visible light communication system[C]//SPIE Defense and Commercial Sensing, 2020.
[15] HARDY N. Demonstration of vehicle-to-vehicle optical pointing, acquisition, and tracking for undersea laser communications[C]//Proceedings of the SPIE, 2019.
[16] SUPUN R, TOBY S, HENRIK S. Construction of a high-resolution under-ice AUV navigation framework using a multidisciplinary virtual environment[C]//IEEE/OES Autonomous Underwater Vehicle Symposium, 2020.
[17] SUPUN R. A high-resolution AUV navigation framework with integrated communication and tracking for under-ice deployments[J]. Journal of Field Robotics, 2020, 40(2): 346-367.
[18] JESSE R P. AUV-assisted diver navigation[C]//IEEE Robotics and Automation Letters, 2022.
[19] I KVASIĆ. Aided diver navigation using autonomous vehicles in simulated underwater environment[J]. Journal of Marine Science and Engineering, 2020, 8(16): 413.
[20] MATTEO B. ASV acoustically tracking and following an AUV: preliminary experimental evaluation[J]. IEEE Journal of Oceanic Engineering, 2021, 35(4): 971-983.
[21] SETH M. Ocean front detection and tracking using a team of heterogeneous marine vehicles[J]. Journal of Field Robotics, 2021, 38(6): 854-881.
[22] JO YUN-JAE. Omparison of velocity obstacle and artificial potential field methods for collision avoidance in swarm operation of unmanned surface vehicles[J]. Journal of Marine Science & Engineering, 2022, 12: 2036.
[23] CHARIS N. A swarm intelligence graph-based pathfinding algorithm based on fuzzy logic (SIGPAF): a case study on unmanned surface vehicle multi-objective path planning[J]. Journal of Marine Science and Engineering, 2021, 9(11): 1243.