基于局部流场构建的水下滑翔机路径规划

doi:10.13973/j.cnki.robot.170130

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周耀鉴, 刘世杰, 俞建成, 王晓辉. 基于局部流场构建的水下滑翔机路径规划[J]. 机器人, 2018, 40(1): 1-7.DOI: 10.13973/j.cnki.robot.170130. ZHOU Yaojian, LIU Shijie, YU Jiancheng, WANG Xiaohui. Underwater Glider Path Planning Based on Local Flow Field Construction. ROBOT, 2018, 40(1): 1-7. DOI: 10.13973/j.cnki.robot.170130.

摘要提出了一种基于局部流场构建的水下滑翔机路径规划方法．首先，基于历史剖面的深平均流对未来剖面的深平均流进行预测，并进行位置确定，然后将最前方若干周期的深平均流作为观测值，结合客观分析技术来构建局部流场．最后以构建的流场为基础，采用CTS-A^*（constant time surfacing A^*）迭代算法进行路径规划．在仿真环境下，分别利用该路径规划算法对单个流场和多个流场进行测试，并对结果进行了分析．实验结果表明，该路径规划算法适用于常规大小海流以及大海流情形．

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	周耀鉴
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关键词 ：水下滑翔机, 路径规划, 局部流场构建

Abstract：A path planning method for underwater glider is proposed based on local flow field construction. Firstly, the depth-averaged currents from the future profiles are predicted based on the depth-averaged currents from the historical profiles, and their positions are determined as well. Then several depth-averaged currents from the top profiles are taken as the observations, and a local flow field is constructed by the objective analysis technology. Finally, CTS-A^* (constant time surfacing A^*) iterative algorithm is applied to path planning based on the constructed flow field. In the simulation environments, the path planning method is tested in a single flow map and numerous flow maps, and the results are analyzed. The results show that the path planning method can apply to the situations of ordinary ocean currents and strong ocean currents.

Key words： underwater glider path planning local flow field construction

收稿日期: 2017-03-11 录用日期: 2017-08-24

TP24

基金资助:国家自然科学基金重点项目（612330131）

通讯作者: 俞建成,yjc@sia.cn E-mail: yjc@sia.cn

作者简介: 周耀鉴(1987-),男,博士生.研究领域:水下机器人导航与路径规划;
刘世杰(1989-),男,博士生.研究领域:水下机器人观测行为优化;
俞建成(1976-),男,博士,研究员.研究领域:水下机器人导航、控制,载体设计.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.170130 或 https://robot.sia.cn/CN/Y2018/V40/I1/1

[1] Webb D C, Simonetti P J, Jones C P. SLOCUM:An underwater glider propelled by environmental energy[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4):447-452.
[2] Eriksen C C, Osse T J, Light R D, et al. Seaglider:A long-range autonomous underwater vehicle for oceanographic research[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4):424-436.
[3] Sherman J, Davis R E, Owens W B, et al. The autonomous underwater glider "Spray"[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4):437-446.
[4] Kruger D, Stolkin R, Blum A, et al. Optimal AUV path planning for extended missions in complex, fast-flowing estuarine environments[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 2007:4265-4270.
[5] Fernández-Perdomo E, Cabrera-Gámez J, Hernández-Sosa D, et al. Path planning for gliders using regional ocean models:Application of Pinzón path planner with the ESEOAT model and the RU27 trans-Atlantic flight data[C]//OCEANS 2010. Piscataway, USA:IEEE, 2010:10pp.
[6] Rao D, Williams S B. Large-scale path planning for underwater gliders in ocean currents[C]//Australasian Conference on Robotics and Automation. Australia:Australian Robotics and Automation Association Inc., 2009.
[7] Pereira A A, Binney J, Hollinger G A, et al. Risk-aware path planning for autonomous underwater vehicles using predictive ocean models[J]. Journal of Field Robotics, 2013, 30(5):741-762.
[8] Merckelbach L M, Briggs R D, Smeed D A, et al. Current measurements from autonomous underwater gliders[C]//IEEE/OES/CMTC Ninth Working Conference on Current Measurement Technology. Piscataway, USA:IEEE, 2008:61-67.
[9] Zhou Y J, Yu J C, Wang X H. Time series prediction methods for depth-averaged current velocities of underwater gliders[J]. IEEE Access, 2017, 5:5773-5784.
[10] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London, A:Mathematical, Physical and Engineering Sciences, 1998, 454(1971):903-995.
[11] 王跃山.客观分析和四维同化——站在新世纪的回望(I)客观分析概念辨析[J].气象科技,2000,28(3):1-8.Wang Y S. Objective analysis and 4D VAR-Looking back at the beginning of the new century (I):Analysis about the concept of objective analysis[J]. Meteorological Science and Technology, 2000, 28(3):1-8.
[12] Leonard N E, Paley D A, Lekien F, et al. Collective motion, sensor networks, and ocean sampling[J]. Proceedings of the IEEE, 2007, 95(1):48-74.
[13] Leonard N E, Paley D A, Davis R E, et al. Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay[J]. Journal of Field Robotics, 2010, 27(6):718-740.
[14] Huang Y, Yu J C, Zhao W T, et al. A practical path tracking method for autonomous underwater gilders using iterative algorithm[C]//OCEANS 2015. Piscataway, USA:IEEE, 2015:360-364.
[15] Liang X L, Wu W C, Chang D, et al. Real-time modelling of tidal current for navigating underwater glider sensing networks[M]//Procedia Computer Science, vol.10. Amsterdam, Netherlands:Elsevier, 2012:1121-1126.