A Simulation Environment for Deep-Sea Hydrothermal Plume Tracing withAutonomous Underwater Vehicles
TIAN Yu1,2, LI Wei1, ZHANG Aiqun1
1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
2. Graduate School of the Chinese Academy of Sciences, Beijing 100049, China
For using an autonomous underwater vehicle (AUV) to localize seafloor hydrothermal vents fast and accurately, a biomimetic approach to hydrothermal plume tracing is proposed. And to support the investigation of AUV's biologically-inspired control strategies, a graphical simulation environment is designed and developed. In this paper, hydrothermal plume tracing with AUVs and the modular architecture of the simulation environment are firstly introduced and described. Then, the modules of hydrothermal plume and flow field in simulation environment are modeled, and the efficient numerical solution algorithms are given. To facilitate Monte Carlo simulation, a set of stochastic initial and boundary conditions are set. And the modular behavior-based AUV control system architecture employed in the control system module is mainly described. The simulation environment addresses the key factors that complicate the investigation of AUV's biologically-inspired control strategies for the hydrothermal plume tracing, including the current field being non-uniform and non-steady, the plume distribution being irregular, intermittent and of large scale, the plume centreline being meandrous, and the plume containing buoyant part and nonconservative tracer. In addition, this simulation environment achieves good visual effect and high computational efficiency, which allows it to be suitable for real-time simulation and Monte Carlo simulation studies. The presented simulation environment provides sufficient support for the investigation of AUV's biologically-inspired control strategies for hydrothermal plume tracing.
[1] 杜同军,翟世奎,任建国.海底热液活动与海洋科学研究 [J].青岛海洋大学学报,2002,32(4): 597-602. Du T J, Zhai S K, Ren J G. Studies on the seafloor hydrothermal activity and ocean science [J]. Journal of Ocean University of Qingdao, 2002, 32(4): 597-602.
[2] 夏建新,李畅,马彦芳.深海底热液活动研究热点 [J].地质力学学报,2007,13(2): 179-191. Xia J X, Li C, Ma Y F. Deep-sea hydrothermal activity: A hot research topic [J]. Journal of Geomechanics, 2007, 13(2): 179-191.
[3] 杨作升,范德江,李云海,等.热液羽状流研究进展 [J].地球科学进展,2006,21(10):999-1007. Yang Z S, Fan D J, Li Y H, et al. Advances in hydrothermal plumes study [J]. Advances in Earth Science, 2006, 21(10): 999-1007
[4] 翟世奎,李怀明,于增慧,等.现代海底热液活动调查研究技术进展 [J].地球科学进展,2007,22(8):769-776. Zhai S K, Li H M, Yu Z H, et al. Advances in the investigation technology of modern seafloor hydrothermal activities [J]. Advances in Earth Science, 2007, 22(8): 769-776.
[5] Jakuba M V. Stochastic mapping for chemical plume source localization with application to autonomous hydrothermal vent discovery [D]. USA: WHOI-MIT, 2007.
[6] German C R, Yoerger D R, Jakuba M, et al. Hydrothermal exploration by AUV: Progress to-data with ABE in the Pacific, Atlantic & Indian Oceans [C]//IEEE/OES Autonomous Underwater Vehicles. Piscataway, NJ, USA: IEEE, 2008: 1-5.
[7] McPhail S, Stevenson P, Pebody M, et al. Challenges of using an AUV to find and map hydrothermal vent sites in deep and rugged terrains [C]//Autonomous Underwater Vehicles, 2010 IEEE/OES. Piscataway, NJ, USA: IEEE, 2010: 1-8.
[8] Yoerger D R, Bradley A M, Jakuba M V, et al. Autonomous and remotely operated vehicle technology for hydrothermal vent discovery, exploration, and sampling [J]. Oceanography, 2007, 20(1): 152-161.
[9] Baker E T, German C R, Elderfield H. Hydrothermal plumes over spreading-center axes: Global distributions and geological inference [M]//Humphris S E, Zierenberg R A, Mullineaux L S, et al. Seafloor hydrothermal systems: Physical, chemical, biological, and geological interactions. Washington DC, WA, USA: American Geophysical Union, 1995: 47-71.
[10] Yoerger D R, Jakuba M V, Bradley A M, et al. Techniques for deep sea near bottom survey using an autonomous underwater vehicle [J]. International Journal of Robotics Research, 2007, 26(1): 41-54.
[11] Pang S. Plume source localization for AUV based autonomous hydrothermal vent discovery [C]//Oceans 2010. Piscataway, NJ, USA: IEEE, 2010: 1-8.
[12] Saigol Z A, Dearden R W, Wyatt J L, et al. Information-lookahead planning for AUV mapping [C]//21st International Joint Conference on Artificial Intelligence. Heidelberg, Germany: Springer, 2009: 1831-1836.
[13] Naeem W, Sutton R, Chudley J. Chemical plume tracing and odour source localisation by autonomous vehicles [J]. The Journal of Navigation, 2007, 60(2): 173-190.
[14] Kowadlo G, Russell R A. Robot odor localization: A taxonomy and survey [J]. International Journal of Robotics Research, 2008, 27(8): 869-894.
[15] Farrell J A, Pang S, Li W. Chemical plume tracing via an autonomous underwater vehicle [J]. IEEE Journal of Oceanic Engineering, 2005, 30(2): 428-442.
[16] Li W, Farrell J A, Pang S, et al. Moth-inspired chemical plume tracing on an autonomous underwater vehicle [J]. IEEE Transactions on Robotics, 2006, 22(2): 292-307.
[17] Jakuba M, Yoerger D, Bradley A, et al. Multiscale, multimodal AUV surveys for hydrothermal vent localization [C]//14th International Symposium on Unmanned Untethered Submersible Technology. 2005.
[18] Li W, Farrell J A, Cardé R T. Tracking of fluid-advected odor plumes: Strategies inspired by insect orientation to pheromone [J]. Adaptive Behavior, 2001, 9(3/4): 143-170.
[19] Farrell J A, Murlis J, Long X, et al. Filament-based atmospheric dispersion model to achieve short time-scale structure of odor plumes [J]. Environmental Fluid Mechanics, 2002, 2: 143-169.
[20] Liu Z, Lu T F. A simulation framework for plume-tracing research [C]//The 2008 Australian Conference on Robotics & Automation. 2008: 1-7.
[21] Porter III M J, Vasquez J R. Bio-inspired navigation of chemical plumes [C]//9th International Conference on Information Fusion. Piscataway, NJ, USA: IEEE, 2006: 1-8.
[22] 张兆顺,崔桂香,许春晓.湍流理论与模拟 [M].北京:清华大学出版社,2005. Zhang Z S, Cui G X, Xu C X. Theory and modeling of turbulence [M]. Beijing: Tsinghua Universigy Press, 2005.
[23] Mestres M. Three-dimensional simulation of pollutant dispersion in coastal waters [D]. Barcelona, Spain: Universitat Politécnica de Catalunya, 2002.
[24] Anfossi D. Analysis of plume rise data from five TVA steam plants [J]. Journal of Applied Meteorology, 1985, 24(11): 1225-1236.
[25] Bennett A A, Leonard J J. A behavior-based approach to adaptive feature detection and following with autonomous underwater vehicles [J]. IEEE Journal of Oceanic Engineering, 2000, 25(2): 213-226.
[26] Tian Y, Zhang A Q. Development of a guidance and control system for an underwater plume exploring AUV [C]//8th World Congress on Intelligent Control and Automation. Piscataway: IEEE, 2010: 6666-6670.
[27] Tian Y, Li W, Zhang A Q, et al. Behavior-based control of an autonomous underwater vehicle for adaptive plume mapping [C]//The 2nd International Conference on Intelligent Control and Information Processing. Piscataway, NJ, USA: IEEE, 2011: 719-724.
[28] Li W. Identifying an odour source in fluid-advected environments, algorithms abstracted from moth-inspired plume tracing strategies [J]. Applied Bionics and Biomechanics, 2010, 7(1): 3-17.
[29] Li W, Carter D. Subsumption architecture for fluid-advected chemical plume tracing with soft obstacle avoidance [C]// Oceans 2006. Piscataway, NJ, USA: IEEE, 2006.
