田宇, 李伟, 张艾群. 自主水下机器人深海热液羽流追踪仿真环境[J]. 机器人, 2012, 34(2): 159-169,196. DOI: 10.3724/SP.J.1218.2012.00159
引用本文: 田宇, 李伟, 张艾群. 自主水下机器人深海热液羽流追踪仿真环境[J]. 机器人, 2012, 34(2): 159-169,196. DOI: 10.3724/SP.J.1218.2012.00159
TIAN Yu, LI Wei, ZHANG Aiqun. A Simulation Environment for Deep-Sea Hydrothermal Plume Tracing withAutonomous Underwater Vehicles[J]. ROBOT, 2012, 34(2): 159-169,196. DOI: 10.3724/SP.J.1218.2012.00159
Citation: TIAN Yu, LI Wei, ZHANG Aiqun. A Simulation Environment for Deep-Sea Hydrothermal Plume Tracing withAutonomous Underwater Vehicles[J]. ROBOT, 2012, 34(2): 159-169,196. DOI: 10.3724/SP.J.1218.2012.00159

自主水下机器人深海热液羽流追踪仿真环境

A Simulation Environment for Deep-Sea Hydrothermal Plume Tracing withAutonomous Underwater Vehicles

  • 摘要: 提出用自主水下机器人(autonomous underwater vehicle,AUV)基于仿生行为追踪深海热液羽流,进而快速、精确定位海底热液喷口; 并针对AUV追踪深海热液羽流的仿生控制策略研究需要, 设计、实现了一个计算机仿真环境. 首先介绍了基于AUV的深海热液羽流追踪和该仿真环境的模块化构成, 然后给出了仿真环境中的流场和羽流仿真模块所采用的仿真模型及其高效的数值求解算法,和 为便于蒙特卡洛仿真而设置的一组随机初始条件和边界条件, 以及介绍了控制系统仿真模块采用的一种基于行为的模块化的AUV控制系统体系结构. 该仿真环境体现了AUV追踪热液羽流的仿生控制策略研究的问题复杂性因素,包括流场非均匀和非定常,羽流分布不规则、不连续、空间尺度大,羽流轴线弯曲,以及羽流含有浮力上升部分和包含非守恒示踪物质,并且具有较好的可视化效果.同时,该仿真环境具有较高的计算效率,适合于实时仿真和 蒙特卡洛仿真研究.分析和演示表明,该仿真环境满足研究需要,为AUV追踪深海热液羽流的仿生控制策略研究提供了有力的支持.

     

    Abstract: 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.

     

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