Progress of Underwater Plume Tracking Methods

XU Xue-han; MENG Qing-hao; LIU Ke-xian; JING Tao

doi:10.11993/j.issn.2096-3920.2022.01.001

Volume 30 Issue 1

Feb 2022

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XU Xue-han, MENG Qing-hao, LIU Ke-xian, JING Tao. Progress of Underwater Plume Tracking Methods[J]. Journal of Unmanned Undersea Systems, 2022, 30(1): 1-14. doi: 10.11993/j.issn.2096-3920.2022.01.001

Citation:

XU Xue-han, MENG Qing-hao, LIU Ke-xian, JING Tao. Progress of Underwater Plume Tracking Methods[J]. Journal of Unmanned Undersea Systems, 2022, 30(1): 1-14. doi: 10.11993/j.issn.2096-3920.2022.01.001

XU Xue-han, MENG Qing-hao, LIU Ke-xian, JING Tao. Progress of Underwater Plume Tracking Methods[J]. Journal of Unmanned Undersea Systems, 2022, 30(1): 1-14. doi: 10.11993/j.issn.2096-3920.2022.01.001

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Progress of Underwater Plume Tracking Methods

doi: 10.11993/j.issn.2096-3920.2022.01.001

Institute of Robotics and Autonomous Systems, School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China

Received Date: 2021-07-07
Rev Recd Date: 2021-08-26
Publish Date: 2022-02-28

Abstract

Abstract

There has been significant research on underwater plume for marine resource exploitation and environmental protection. Based on underwater plume dispersion modeling and tracking methods, the existing relevant research results, research progress, and development trend of underwater plume tracking were summarized. Firstly, the classification of underwater plumes and application background of plume tracking were presented. Subsequently, the research status of underwater plume dispersion modeling was reviewed from two aspects: The dispersion model and simulation platform. Thirdly, the current underwater plume tracking methods were divided into three categories, namely the reactive, probability estimation, and reinforcement learning methods, and the representative research were reviewed. Finally, the development trend of underwater plume tracking research was discussed. This review could provide a reference for further research on underwater plume tracking.
- underwater plume,
- dispersion modeling,
- plume tracking

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References

[1]	Dover C L V. Impacts of Anthropogenic Disturbances at Deep-Sea Hydrothermal Vent Ecosystems: A Review[J]. Marine Environmental Research, 2014, 102: 59-72.
[2]	Jakuba M V. Stochastic Mapping for Chemical Plume Source Localization with Application to Autonomous Hydrothermal Vent Discovery[D]. USA: Massachusetts Institute of Technology, 2007.
[3]	Aryadi Y, Rizal I S, Fadhli M N. Electricity Generation from Hydrothermal vents[C]//IOP Conference Series: Earth and Environmental Science. Indonesia: IOP Publishing, 2016.
[4]	Talukder A R. Review of Submarine Cold Seep Plumbing Systems: Leakage to Seepage and Venting[J]. Terra Nova, 2012, 24(4): 255-272.
[5]	Leifer I. A Synthesis Review of Emissions and Fates for the Coal Oil Point Marine Hydrocarbon Seep Field and California Marine Seepage[J]. Geofluids, 2019(5): 1-48.
[6]	Hwang J, Bose N, Nguyen H D, et al. Acoustic Search and Detection of Oil Plumes Using an Autonomous Underwater Vehicle[J]. Journal of Marine Science and Engineering, 2020, 8(8): 618.
[7]	Wang Q, Yang Z. Industrial Water Pollution, Water Environment Treatment, and Health Risks in China[J]. Environmental Pollution, 2016, 218(11): 358-365.
[8]	Russell R A, Bab-Hadiashar A, Shepherd R L, et al. A Comparison of Reactive Robot Chemotaxis Algorithms[J]. Robotics and Autonomous Systems, 2003, 45(2): 83-97.
[9]	孟庆浩, 李飞. 主动嗅觉研究现状[J]. 机器人, 2006, 28(1): 89-96. Meng Qing-hao, Li Fei. Review of Active Olfaction[J]. Robot, 2006, 28(1): 89-96.
[10]	Kowadlo G, Russell R A. Robot Odor Localization: a Taxonomy and Survey[J]. The International Journal of Robotics Research, 2008, 27(8): 869-894.
[11]	Ishida H, Wada Y, Matsukura H. Chemical Sensing in Robotic Applications: A Review[J]. IEEE Sensors Journal, 2012, 12(11): 3163-3173.
[12]	Chen X X, Huang J. Odor Source Localization Algorithms on Mobile Robots: A Review and Future Outlook[J]. Robotics and Autonomous Systems, 2019, 112: 123-136.
[13]	Jing T, Meng Q H, Ishida H. Recent Progress and Trend of Robot Odor Source Localization[J]. IEEJ Transactions on Electrical and Electronic Engineering, 2021, 16(7): 938-953.
[14]	Ji C, Beegle-Krause C J, Englehardt J D. Formation, Detection, and Modeling of Submerged Oil: A Review[J]. Journal of Marine Science and Engineering, 2020, 8(9): 642.
[15]	韩同刚, 童思友, 陈江欣, 等. 海底羽状流探测方法分析[J]. 地球物理学进展, 2018, 33(5): 2113-2125. Han Tong-gang, Tong Si-you, Chen Jiang-xin, et al. Analysis of Detection Methods for Submarine Plume[J]. Progress in Geophysics, 2018, 33(5): 2113-2125.
[16]	马媛媛, 辛洋, 蒋磊. 海底热液喷口流体中H2S浓度数据统计及其探测技术进展[J]. 海洋科学, 2020, 44(2): 146-160. Ma Yuan-yuan, Xin Yang, Jiang Lei. Concentration Statistics and Detection Technology of Hydrogen Sulfide in Submarine Hydrothermal Vent Fluids[J]. Marine Science, 2020, 44(2): 146-160.
[17]	刘国栋, 王焱. 环境水力学[M]. 北京: 中国水利水电出版社, 2018.
[18]	Petillo S M, Schmidt H. Autonomous and Adaptive Underwater Plume Detection and Tracking with AUVs: Concepts, Methods, and Available Technology[J]. IFAC Proceedings Volumes, 2012, 45(27): 232-237.
[19]	曾志刚, 陈祖兴, 张玉祥, 等. 海底热液活动的环境与产物[J]. 海洋科学, 2020, 44(7): 143-155. Zeng Zhi-gang, Chen Zu-xing, Zhang Yu-xiang, et al. Seafloor Hydrothermal Activities and Their Geological Environments and Products[J]. Marine Science, 2020, 44(7): 143-155.
[20]	李灿苹, 尤加春, 朱文娟. 气泡羽状流的识别及其与资源环境相关性分析[J]. 地球物理学进展, 2016, 31(6): 2747-2755. Li Can-ping, You Jia-chun, Zhu Wen-juan. Identification of Bubble Plumes and Analysis of Its Correlation with Resource Environment[J]. Progress in Geophysics, 2016, 31(6): 2747-2755.
[21]	Leifer I, Patro R K. The Bubble Mechanism for Methane Transport from the Shallow Sea Bed to the Surface: A Review and Sensitivity Study[J]. Continental Shelf Research, 2002, 22(16): 2409-2428.
[22]	Petillo S M, Schmidt H. Autonomous and Adaptive Underwater Plume Detection and Tracking with AUVs: Concepts, Methods, and Available Technology[J]. IFAC Proceedings Volumes, 2012, 45(27): 232-237.
[23]	黄远奕. 我国工业废水重金属灰水足迹的分布特征及驱动因子研究[D]. 北京: 北京科技大学, 2020.
[24]	中华人民共和国生态环境部. 地表水环境质量标准: GB 3838-2002[S]. 北京: 中国标准出版社, 2002.
[25]	Rogowski P, Terrill E, Otero M, et al. Mapping Ocean Outfall Plumes and Their Mixing Using Autonomous Underwater Vehicles[J]. Journal of Geophysical Research Atmospheres, 2012, 117(C7): 1-12.
[26]	Cannell C J, Gadre A S, Stilwell D J. Boundary Tracking and Rapid Mapping of a Thermal Plume Using an Autonomous Vehicle[C]//OCEANS 2006. Boston, MA, USA: IEEE, 2006: 1-6.
[27]	Fahad M, Saul N, Yi G, et al. Robotic Simulation of Dynamic Plume Tracking by Unmanned Surface Vessels[C]//2015 IEEE International Conference on Robotics and Automation (ICRA). Seattle, WA, USA: IEEE, 2015.
[28]	Petillo S M. Autonomous & Adaptive Oceanographic Feature Tracking on Board Autonomous Underwater Vehicles[C]//OCEANS 2015. Genova: IEEE, 2015: 1-10.
[29]	Pang S, Farrell J A. Chemical Plume Source Localization [J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B(Cybernetics), 2006, 36(5): 1068-1080.
[30]	Tian Y, Kang X, Li Y, et al. Identifying Rhodamine Dye Plume Sources in Near-shore Oceanic Environments by Integration of Chemical and Visual Sensors[J]. Sensors, 2013, 13(3): 3776-3798.
[31]	Mysorewala M F, Cheded L, Popa D O. A Distributed Multi-robot Adaptive Sampling Scheme for the Estimation of the Spatial Distribution in Widespread Fields[J]. EURASIP Journal on Wireless Communications and Networking, 2012, 2012(1): 1-19.
[32]	Camilli R, Reddy C M, Yoerger D R, et al. Tracking Hydrocarbon Plume Transport and Biodegradation at Deepwater Horizon[J]. Science, 2010, 330(6001): 201-204.
[33]	Gildner M L. Framework for Multi-vehicle Adaptive Sampling of Jets and Plumes in Coastal Zones[D]. USA: Massachusetts Institute of Technology, 2013.
[34]	Kukulya A L, Bellingham J G, Stokey R P, et al. Autonomous Chemical Plume Detection and Mapping Demonstration Results with a COTS AUV and Sensor Package[C]//MTS/IEEE Charleston OCEANS Conference. Charleston, USA: IEEE, 2018: 1-6.
[35]	Soares D A R, Miguel J. Formation-based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems[R]. Lausanne: EPFL, 2016.
[36]	纠海峰. 基于水下机器人的热液羽状流自主搜寻定位方法研究[D]. 哈尔滨: 哈尔滨工程大学, 2016.
[37]	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(1): 143-169.
[38]	Balkovsky E, Shraiman B I. Olfactory Search at High Reynolds Number[J]. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(20): 12589-12593.
[39]	王阳. 动态气流环境下气味烟羽仿真与气味源定位[D]. 天津: 天津大学, 2013.
[40]	Boufadel M C, Socolofsky S, Katz J, et al. A Review on Multiphase Underwater Jets and Plumes: Droplets, Hydrodynamics, and Chemistry[J]. Reviews of Geophysics, 2020, 58(3).
[41]	Lesieur M, Metais O. New Trends in Large-eddy Simulations of Turbulence[J]. Annual Review of Fluid Mechanics, 1996, 28(1): 45-82.
[42]	Meneveau C, Katz J. Scale-invariance and Turbulence Models for Large-eddy Simulation[J]. Annual Review of Fluid Mechanics, 2000, 32(1): 1-32.
[43]	温竹青. 基于FLUENT的深海热液羽状流流动模拟[D]. 北京: 中央民族大学, 2011.
[44]	Liu Z, Lu T F. A Simulation Framework for Plume-tracing Research[C]//Proceedings of the 2008 Australasian Conference on Robotics and Automation. Canberra, Australia: ARAA, 2008: 3-5.
[45]	Garg S, Afzulpurkar S, Kumar A. Adaptive Biased Random Walk Algorithm for Ocean Chemical Feature Tracking Using an Autonomous Underwater Vehicle[C]// MTS/IEEE Charleston OCEANS Conference. Charleston, USA: IEEE, 2019: 1-8.
[46]	纠海峰, 庞硕, 韩冰. 热液羽状流模型的建立与仿真[J]. 计算机仿真, 2015, 32(9): 404-408. Jiu Hai-feng, Pang Shuo, Han Bing. Modeling and Simulation of Hydrothermal Plume Model[J]. Computer Simulation, 2015, 32(9): 404-408.
[47]	Fisher M, Dock M. Trace Chemical Sensing of Explosives[M]. New Jersey: John Wiley & Sons, 2006.
[48]	Soares D A R, Miguel J. Formation-based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems[D]. Lausanne: EPFL, 2016.
[49]	Branch A, Guangyu X, Jakuba M V, et al. Autonomous Nested Search for Hydrothermal Venting[C]//International Conference on Automated Planning and Scheduling (ICAPS) 2018, Delft, The Netherlands: AAAI Press, 2018.
[50]	Hwang J, Bose N, Nguyen H D, et al. Oil Plume Mapping: Adaptive Tracking and Adaptive Sampling from an Autonomous Underwater Vehicle[J]. IEEE Access, 2020, 8: 198021-198034.
[51]	田宇, 王昊, 张进, 等. 深海热液探测水下机器人技术:感知、规划与控制[M]．北京: 科学出版社, 2020．
[52]	Han B, Jiu H, Pang S, et al. Hydrothermal Plume Simulation for Autonomous Hydrothermal Vent Discovery[C]//2012 Oceans-Yeosu. Yeosu, Korea(south): IEEE, 2012: 1-7.
[53]	Sutton J, Li W. Development of CPT_M3D for Multiple Chemical Plume Tracing and Source Identification[C]// 2008 Seventh International Conference on Machine Learning and Applications. San Diego, CA, USA: IEEE, 2008: 470-475.
[54]	Tian Y, Zhang A. Simulation Environment and Guidance System for AUV Tracing Chemical Plume in 3-dimensions[C]//2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010). Wuhan: IEEE, 2010: 407-411.
[55]	Arkin R C. Behavior-based Robotics[M]. Cambridge, MA: MIT Press, 1998.
[56]	Burian E, Yoerger D, Bradley A, et al. Gradient Search with Autonomous Underwater Vehicles Using Scalar Measurements[C]//Proceedings of Symposium on Autonomous Underwater Vehicle Technology. Monterey, CA, USA: IEEE, 1996: 86-98.
[57]	Li Z, You K, Song S. AUV Based Source Seeking with Estimated Gradients[J]. Journal of Systems Science and Complexity, 2018, 31(1): 262-275.
[58]	Naeem W, Sutton R, Chudley J. Chemical Plume Tracing and Odour Source Localisation by Autonomous Vehicles[J]. Journal of Navigation, 2007, 60(2): 173-190.
[59]	Hill J, Szewczyk R, Woo A, et al. System Architecture Directions for Network Sensors[J]. ACM SIGOPS Operating Systems Review, 2000, 35(5): 93-104.
[60]	Dhariwal A, Sukhatme G S, Requicha A A G. Bacterium-inspired Robots for Environmental Monitoring[C]//IEEE International Conference on Robotics and Automation, 2004. New Orleans, LA, USA: IEEE, 2004: 1436-1443.
[61]	Grasso F W, Basil J A, Atema J. Toward the Convergence: Robot and Lobster Perspectives of Tracking Odors to Their Source in the Turbulent Marine Environment[C]// Proceedings of the 1998 IEEE International Symposium on Intelligent Control(ISIC) Held Jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation(CIRA) Intell. Gaithersburg, MD, USA: IEEE, 1998: 259-264.
[62]	Jakuba M, Yoerger D, Bradley A, et al. Multiscale, Multimodal AUV Surveys for Hydrothermal Vent Localization[C]//Proceedings of the Fourteenth International Symposium on Unmanned Untethered Submersible Technology (UUST05). 2005.
[63]	Mason J C, Branch A, Xu G Y, et al. Evaluation of AUV Search Strategies for the Localization of Hydrothermal Venting. [EB/OL]. (2020-10-16)[2021-07-07]. https://ica ps20subpages.icaps-conference.org/wp-content/uploads/2020/10/16-PlanRob_2020_paper_13.pdf
[64]	Ferri G, Jakuba M V, Yoerger D R. A Novel Method for Hydrothermal Vents Prospecting Using an Autonomous Underwater Robot[C]//2008 IEEE International Conference on Robotics and Automation. Pasadena, California: IEEE, 2008: 1055-1060.
[65]	Wang L, Pang S, Xu G. 3-Dimensional Hydrothermal Vent Localization Based on Chemical Plume Tracing[C]//Global Oceans 2020: Singapore-US Gulf Coast. Online: IEEE, 2020: 1-7.
[66]	Ai X, You K, Song S. A Source-seeking Strategy for an Autonomous Underwater Vehicle via On-line Field Estimation[C]//2016 14th International Conference on Control, Automation, Robotics and Vision(ICCARV). Phuket, Thailand: IEEE, 2016: 1-6.
[67]	Kramer E. A Tentative Intercausal Nexus and Its Computer Model on Insect Orientation in Windborne Pheromone Plumes[M]//Insect Pheromone Research. Boston, MA: Springer, 1997: 232-247.
[68]	Farrell J A, Pang S, Li W, et al. Chemical Plume Tracing Experimental Results with a REMUS AUV[C]//Oceans 2003. Celebrating the Past Teaming Toward the Future. San Diego, CA, USA: IEEE, 2003: 962-968.
[69]	Farrell J A, Pang S, Wei L. Chemical Plume Tracing via an Autonomous Underwater Vehicle[J]. IEEE Journal of Oceanic Engineering, 2005, 30(2): 428-442.
[70]	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.
[71]	Grasso F W, Atema J. Integration of Flow and Chemical Sensing for Guidance of Autonomous Marine Robots in Turbulent Flows[J]. Environmental Fluid Mechanics, 2002, 2(1): 95-114.
[72]	Farrell J A, Pang S, Li W. Plume Mapping via Hidden Markov Methods[J]. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics, 2003, 33(6): 850-863.
[73]	Jiu H, Chen Y, Deng W, et al. Underwater Chemical Plume Tracing Based on Partially Observable Markov Decision Process[J]. International Journal of Advanced Robotic Systems, 2019, 16(2): 1-12.
[74]	Pang S. Reactive Planning and on-line Mapping for Chemical Plume Tracing[D]. CA, USA: University of California, Riverside, 2004.
[75]	Jakuba M, Yoerger D R. Autonomous Search for Hydrothermal Vent Fields with Occupancy Grid Maps[C]//Proc. of ACRA. 2008, 8: 2008.
[76]	Pang S. Plume Source Localization for AUV Based Autonomous Hydrothermal Vent Discovery[C]//OCEANS 2010 MTS/IEEE SEATTLE. Seattle: IEEE, 2010: 1-8.
[77]	邓薇, 韩端锋, 纠海峰. 基于嗅觉的水下机器人化学羽状物追踪定位方法[J]. 电机与控制学报, 2016(1): 110-118. Deng Wei, Han Duan-feng, Jiu Hai-feng. Chemical Plume Tracing and Localization Method Based on Olfaction for Underwater[J]. Journal of Electric Machines and Control, 2016(1): 110-118.
[78]	Wang L, Pang S. Chemical Plume Tracing Using an AUV Based on POMDP Source Mapping and A-star Path Planning[C]//OCEANS 2019 MTS/IEEE SEATTLE. Seattle: IEEE, 2019: 1-7.
[79]	Sutton R, Barto A. Reinforcement Learning: An Introduction[M]. Cambridge, MA: MIT Press, 1998.
[80]	李金龙. 部分观测马尔可夫决策过程下的深海热液自主探测研究[D]. 哈尔滨: 哈尔滨工程大学, 2013.
[81]	白双. 基于强化学习蚁群算法的主动嗅觉[D]. 天津: 天津大学, 2009.
[82]	Niu L, Song S, You K. A Plume-tracing Strategy via Continuous State-action Reinforcement Learning[C]//2017 Chinese Automation Congress. Jinan, China: IEEE, 2017: 759-764.
[83]	Hu H, Song S, Chen C L P. Plume Tracing via Model-free Reinforcement Learning Method[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(8): 2515-2527.
[84]	Wang L, Pang S, Li J. Olfactory-based Navigation via Model-based Reinforcement Learning and Fuzzy Inference Methods[J]. IEEE Transactions on Fuzzy Systems, 2021, 29(10): 3014-3027.
[85]	Tang S, Guo A. Choice Behavior of Drosophila Facing Contradictory Visual Cues[J]. Science, 2001, 294(5546): 1543-1547.

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