Research on Landing Strategy and Influencing Factors of
 an Autonomous Underwater Vehicle with Supporting Mechanism

doi:10.16183/j.cnki.jsjtu.2017.10.014

Abstract

Abstract: Conception and working process of an autonomous underwater vehicle (AUV) that can park on the seabed were introduced briefly. Kinematic and dynamic mathematical models of the AUV spatial motion were established based on basic mechanics theory. Combined with the characteristics of this AUV, forces’ mathematic models of variable buoyancy system and vertical thrusters were established, and control algorithm of verticalthrusters was designed. Based on this, landing simulation model was established. Four landing strategies of the AUV with supporting mechanism were proposed: diving freely with negative buoyancy, diving freely with supporting mechanics with negative buoyancy, diving under the control of vertical thrusters and diving with supporting mechanics under the control of vertical thrusters. On this basis, the impact of mass and position of water injected into the AUV on landing parameters were studied. Finally, the influences of supporting mechanism and vertical thrusters were analyzed through comparing different landing strategies. Results in this paper provide theoretical basis to landing program design and improvement of the AUV.

Key words: autonomous underwater vehicle (AUV), landing strategy, supporting mechanism, vertical thrusters, spatial motion model

CLC Number:

TP 242.3

ZHU Xinyao1，SONG Baowei2,XU Gang1,YANG Songlin1. Research on Landing Strategy and Influencing Factors of
an Autonomous Underwater Vehicle with Supporting Mechanism[J]. Journal of Shanghai Jiaotong University, 2017, 51(10): 1241-1251.

References

［1］HEALEY A J, MARCO D B. Experimental verification of mission planning by autonomous mission execution and data visualization using the NPS AUV II［C］ ∥Proceedings of IEEE Oceanic Engineering Society Symposium on Autonomous Underwater Vehicles. Washington D C: IEEE, 1992: 6572.
［2］RIEDEL J S, HEALEY A J, MARCO D B, et al. Design and development of low cost variable buoyancy system for the soft grounding of autonomous underwater vehicles ［R］. Monterey CA: Naval Postgraduate School, Monterey CA Center for Autonomous Underwater Vehicle Research, 2005.
［3］STEWART A L G, MARC P O, ROBERT K C, et al. A passive sonar system based on an autonomous underwater vehicle ［J］. IEEE Journal of Oceanic Engineering, 2001, 26(4): 700710.
［4］SANGEKAR M N, THORNTON B, NAKATANI T, et al. Development of a landing algorithm for autonomous underwater vehicles using laser profiling［C］∥OCEANS 2010. Sydney: IEEE 2010: 17.
［5］SANGEKAR M, THORNTON B, URA T. Wide area seafloor observation using an autonomous landing vehicle with adaptive resolution capability ［C］∥OCEANS. IEEE, 2012: 19.
［6］NIEWIADOMSKA K, JONES C, WEBB D. Design of a mobile and bottom resting autonomous underwater gliding vehicle［C］∥Proceedings of the 13th International Symposium on Unmanned Untethered Submersible Technology. Durham New Hampshire: Autonomous Undersea Systems Institute, 2003.
［7］侯巍. 具有着陆坐底功能的水下自航行器系统控制与试验研究［D］. 天津: 天津大学机械工程学院, 2006.
［8］王晓明, 王树新, 张宏伟, 等. AUV水下着陆策略研究［J］.机器人, 2008, 30(4): 347352.
WANG Xiaoming, WANG Shuxin, ZHANG Hongwei, et al. Research on the underwater landing strategy of AUV ［J］. Robot, 2008, 30(4): 347352.
［9］王晓明, 张宏伟, 王树新, 等. 基于模糊控制的水下自航行器着陆策略分析［J］. 机械工程学报, 2009, 45(3): 8488.
WANG Xiaoming, ZHANG Hongwei, WANG Shuxin, et al. Analysis on the landing strategy of autonomous underwater vehicle based on fuzzy control ［J］. Journal of Mechanical Engineering, 2009, 45(3): 8488.
［10］宋保维, 朱信尧, 曹永辉, 等. UUV海底定点停驻策略及其关键技术［J］. 鱼雷技术, 2010, 18（6）: 401405.
SONG Baowei, ZHU Xinyao, CAO Yonghui, et al. Strategy and key technologies of UUV parking on the seabed ［J］ . Torpedo Technology, 2010, 18（6）: 401405.
［11］KIM D, CHOI H S, KIM J Y, et al. Trajectory generation and slidingmode controller design of an underwater vehiclemanipulator system with redundancy［J］. International Journal of Precision Engineering and Manufacturing, 2015, 16 (7): 15611570.
［12］李天森. 鱼雷操纵性.第2版［M］. 北京: 国防工业出版社, 2007.
［13］朱信尧, 宋保维, 单志雄, 等. 海底定点停驻无人水下航行器流体动力特性分析［J］. 上海交通大学学报, 2012, 46(4): 573578.

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