AUV归航和坐落式对接的半物理仿真

doi:10.13973/j.cnki.robot.2017.0119

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (914 KB) HTML ( ) 输出: BibTeX \| EndNote (RIS)
引用本文:
李晔, 何佳雨, 姜言清, 安力. AUV归航和坐落式对接的半物理仿真[J]. 机器人, 2017, 39(1): 119-128.DOI: 10.13973/j.cnki.robot.2017.0119. LI Ye, HE Jiayu, JIANG Yanqing, AN Li. Semi-Physical Simulation of AUV Homing and Docking Processes. ROBOT, 2017, 39(1): 119-128. DOI: 10.13973/j.cnki.robot.2017.0119.

摘要为解决现有仿真系统忽略海流干扰，不能直观反映模型实时运动状态的问题，设计了一套以3维视景方式呈现的半物理仿真系统，以直观地反映归航过程中、以及以类似直升机坐落方式进行对接回收的过程中AUV（自主式水下机器人）的运动状态．利用Multigen Creator软件对AUV和水下地形环境建模，通过VisualC++调用Vega的仿真界面库实现视景仿真；运动控制部分基于B样条理论设计归航时的全局路径规划方法，通过遗传算法搜索满足欠驱动约束的全局路径；利用制导控制和执行控制分层结构设计路径跟踪控制器，其中PID（比例－积分－微分）制导律能依据海流信息自适应调整参考姿态角，S面控制律能针对状态信息和参考姿态角实现稳定、快速、准确的响应．基于试验平台，模拟了AUV从释放位置出发、跟踪所计算出的全局路径从而完成自主归航最终实现坐落式对接的全过程．结果表明：海流在归航阶段对AUV的归航路径跟踪偏差量影响较小，在坐落式对接阶段当海流与AUV艏向相对角度较大时其影响较大，甚至使回收失败．所设计的半物理仿真系统可在海流影响下规划合理的AUV归航路径以完成回收，并实时直观地反映整个过程．

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	李晔
	何佳雨
	姜言清
	安力

关键词 ：自主式水下机器人, 半物理仿真, 路径规划, 水下回收

Abstract：Existing simulation systems ignore the ocean current interference, so that the real-time motion state of the model can't be directly reflected. To solve the problem, a semi-physical simulation system based on 3D visual scene is designed to directly display the motion states of the AUV (autonomous underwater vehicle) during the homing process and the recovery process through docking like a helicopter landing. The AUV and the underwater terrain are modeled using Multigen Creator software. The visual simulation is realized by calling the simulation interface library functions of Vega software in Visual C++. For motion control, a global path planning method for homing is designed based on B-spline theory, and a global path satisfying underactuation constraints is searched by genetic algorithm. A path tracking controller is designed by the layered structure of guidance control and executive control, in which the PID (proportional-integral-differential) guidance law can adjust the reference attitude angle according to the ocean current information, and the S-plane control law can make stable, fast and accurate response to the status information and the reference attitude angle. All the processes are simulated on the test platform, including the AUV starting from the release position, autonomously homing by tracking the calculated global path, till docking. The results show that the influence of ocean current on the path tracking deviation of AUV is small in homing process, but its influence in docking process is very large when the relative angle between the ocean current and the heading direction is big, which maybe cause a recovery failure. A reasonable homing path can be planned for AUV to complete the recovery process under the influence of ocean current, and all the processes can be directly reflected in real-time in the designed semi-physical simulation system.

Key words： autonomous underwater vehicle semi-physical simulation path planning underwater recovery

收稿日期: 2016-09-09 录用日期: 2017-01-03

TP242.6

基金资助:国家自然科学基金（51279221，51579022）

通讯作者: 何佳雨，hjy2011@hrbeu.edu.cn E-mail: hjy2011@hrbeu.edu.cn

作者简介: 李晔（1978-），男，博士，教授．研究领域：潜艇潜器操纵性与运动控制，海底地形匹配导航，低能耗水下、水面无人系统．
何佳雨（1993-），男，博士生．研究领域：AUV智能规划与运动控制，视景仿真，操纵性仿真．

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.2017.0119 或 https://robot.sia.cn/CN/Y2017/V39/I1/119

[1] 燕奎臣,吴利红.AUV水下对接关键技术研究[J].机器人,2007,29(3):267-273.Yan K C, Wu L H. Research on the key technology of AUV underwater docking[J]. Robot, 2007, 29(3):267-273.
[2] Singh H, James G. Docking for an autonomous ocean sampling network[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4):498-514.
[3] Martin S, Fletcher B, Flores G, et al. Characterizing the critical parameters for docking unmanned underwater vehicles[C]//OCEANS 2016. Piscataway, USA:IEEE, 2016:doi:10.1109/OCEANS.2016.7761451.
[4] Kawasaki T, Noguchi T, Fukasawa T, et al. "Marine Bird", a new experimental AUV——Results of docking and electric power supply tests in sea trials[C]//OCEANS 2004, vol.3. Piscataway, USA:IEEE, 2016:1738-1744.
[5] Chong L, Pang Y J, Li Y, et al. Improved S surface controller and semi-physical simulation for AUV[J]. Journal of Marine Science and Application, 2010, 9(3):301-306.
[6] 李一鸣.AUV自主对接路径规划与半物理仿真系统研究[D].哈尔滨:哈尔滨工程大学,2013.Li Y M. Research on the path planning and semi physical simulation system of AUV autonomous docking[D]. Harbin:Harbin Engineering University, 2013.
[7] Dierks T, Jagannathan S. Output feedback control of a quad rotor UAV using neural networks[J]. IEEE Transactions on Neural Networks, 2010, 21(1):50-66.
[8] Aneke N P I, Nijmejier H, de Jager A G. Tracking control of second-order chained form systems by cascaded back stepping linearization[J]. IEEE Transactions on Robotics, 2005, 21(3):505-513.
[9] Teo K, Goh B, Chai O K. Fuzzy docking guidance using augmented navigation system on an AUV[J]. IEEE Journal of Oceanic Engineering, 2015, 40(2):349-361.
[10] Sun Y, Lei W, Li Y. S plane control based on parameters optimization with simulated annealing for underwater vehicle[C]//International Conference on Electronic and Mechanical Engineering and Information Technology. Piscataway, USA:IEEE, 2011:552-556.
[11] 李晔,姜言清,张国成,等.考虑几何约束的AUV回收路径规划[J].机器人,2015,37(4):478-485.Li Y, Jiang Y Q, Zhang G C, et al. AUV recovery path planning considering geometric constraints[J]. Robot, 2015, 37(4):478-485.
[12] Davis D T. Precision control and maneuvering of the phoenix autonomous underwater vehicle for entering a recovery tube[D/OL]. 1997.[2015-12-01]. http://calhoun.nps.edu/handle/10945/8841.
[13] 张汝波,吴俊伟,刘冠群,等.自主式水下机器人分层规划与重规划[J].华中科技大学学报:自然科学版,2013,41(S1):77-80.Zhang R B, Wu J W, Liu G Q, et al. Hierarchical planning and replanning for autonomous underwater vehicle[J]. Journal of Huazhong University of Science and Technology:Natural Science Edition, 2013, 41(S1):77-80.
[14] 孙晓芳.某智能潜水器操纵性能分析和运动仿真研究[D].哈尔滨:哈尔滨工程大学,2014.Sun X F. Performance analysis and motion simulation of an intelligent submarine[D]. Harbin:Harbin Engineering University, 2014.
[15] Watt G D, Roy A R, Currie J. A concept for docking a UUV with a slowly moving submarine under waves[J]. IEEE Journal of Oceanic Engineering, 2015, 41(2):471-498.
[16] Maki T, Shiroku R T, Sato Y. Docking method for hovering type AUVs by acoustic and visual positioning[C]//IEEE International Symposium on Underwater Technology. Piscataway, USA:IEEE, 2013:1-6.
[17] de Boor C. A practical guide to spline[M]. New York, USA:Springer-Verlag, 1978:131-142.
[18] 姜言清.AUV回收控制的关键技术研究[D].哈尔滨:哈尔滨工程大学,2016.Jiang Y Q. Study on critical control issues for AUV docking applications[D]. Harbin:Harbin Engineering University, 2016.
[19] Valavanis K P, Gracanin D, Matijasevic M, et al. Control architectures for autonomous underwater vehicles[J]. IEEE Control Systems, 1998, 17(6):48-64.
[20] Li Y, Pang Y J. Intelligent PID guidance control for AUV path tracking[J]. Journal of Central South University, 2015, 22(9):3440-3449.
[21] 李岳明,庞永杰,万磊.水下机器人的自适应S面控制[J].上海交通大学学报,2012,46(2):195-200.Li Y M, Pang Y J, Wan L. Adaptive S plane control for autonomous underwater vehicle[J]. Journal of Shanghai Jiaotong University, 2012, 46(2):195-200.