Survey of underwater robot positioning navigation

Underwater robot positioning and navigation achieve autonomous underwater robot movement based on the premise that positioning obtains the coordinates of the relative position of the underwater robot using a sensor, and navigation yields a known location to the destination path planning. Due to the location of an underwater robot and the complex and changing environment in which it operates, it is difficult to achieve precise positioning using the traditional positioning method. This paper systematically analyzes and summarizes several typical localization and navigation methods of underwater robots, such as multisensor information fusion technology, underwater acoustic localization and navigation methods, GPS buoy, underwater vision, SLAM and coordinate localization and navigation of multiple underwater robots. Multisensory information fusion technology integrates the advantages of the above methods, enhances the system stability and robustness, overcomes the disadvantages of traditional positioning and navigation, and enables the autonomous navigation and positioning of underwater robots. Underwater acoustics enable flexible and convenient positioning, whereas GPS can achieve high-precision and high-positioning navigation information, and visual positioning effectively overcomes the problem of error accumulation. Multirobot cooperative positioning resolves the problem of positioning failure caused by the collapse of a single system and completes complex tasks that cannot be completed by a single robot, thus enhancing the stability and robustness of the system. This paper systematically describes the realization of these methods, presents an actual analysis of their respective advantages and problems, and discusses the development of the field of research prospects and application prospects.     

水下仿生扑翼机器人的发展现状综述

参照蝠鲼等鱼类游动方式所研制的水下仿生扑翼机器人具有效率高、机动性强、负载能力大等多方面优势。由于其广阔的应用前景,水下仿生扑翼机器人已逐步成为水下航行器领域的研究热点。本文系统地将蝠鲼的生物学特性、机器人的结构设计、动力学模型、单体运动控制、集群运动控制以及实验研究等方面的国内外研究进展进行了总结和梳理。已有的研究表明：水下仿生扑翼机器人正在朝着软体化、集群化、 高机动等方向发展,新兴的水下仿生扑翼机器人及仿生集群能够更加精确的模拟真实生物的游动姿态,并开展相关任务。当下的研究为水下仿生扑翼机器人性能的进一步优化与提升奠定了坚实的理论与实践基础。     

水下机器人标准体系框架构建探索

水下机器人作为一类特种机器人,日益成为探索海洋奥秘、开发海洋资源的重要工具,被称为海洋高技术的皇冠,正逐步成为国家间海洋技术竞争的制高点。水下机器人标准体系最直接的作用是指导、规范水下机器人标准制定工作,使人们清楚水下机器人标准化工作方向和重点,有助于推动水下机器人研发和产业化进程,促进快速、健康发展。文章在介绍国内外水下机器人标准制订的基础上,探讨水下机器人标准体系框架构建思路,提出标准体系建设路径,明确水下机器人标准化工作范围和领域,并构建了水下机器人标准体系序列结构、三维结构、层次结构3种框架模型,为构建我国水下机器人标准体系提供了有价值的参考。     

基于模糊神经网络理论对水下拖曳体进行深度轨迹控制

以华南理工大学开发的自主稳定可控制水下拖曳体为研究对象,首先通过水下拖曳体在拖曳水池样机中的试验取得试验数据后作为训练样本,采用LM BP算法,建立基于神经网络理论构建的可控制水下拖曳体轨迹与姿态水动力的数值模型。在此基础上设计了一个控制系统,它主要由两部分组成:基于遗传算法的神经网络辨识器和基于模拟退火改进的遗传算法的模糊神经网络控制器。以满足预先设定的拖曳体水下监测轨迹要求为控制依据,由控制系统确定为达到所要求的运动轨迹而应采用的迫沉水翼转角,以此作为输入参数,通过LM BP神经网络模型的模拟计算预报在这一操纵动作控制下的拖曳体所表现的轨迹与姿态特征。数值模拟计算结果表明:该系统的设计达到了所要求的目的;借助这一系统,可以有效地实现对拖曳体的深度轨迹控制。     

葫芦岛港柳条沟港区规划潮流泥沙数模研究

建立了基于不规则三角形网格的考虑波浪作用的潮流泥沙数学模型,在对模型进行充分验证的基础上,对葫芦岛海域的潮流、泥沙场的进行了数值模拟,对该海区的潮流扬、泥沙场特征进行了分析;对萌芦岛港柳条沟港区规划方案进行了潮流、泥沙场模拟研究。详细分析了工程前后港池和航道的流扬变化,计算了航道的横流,预报了规划港区港池和航道的泥沙年淤积量,为港区的规划设计提供了科学依据。     

深海大型爬行机器人研究现状

对海底不同作业形式的深海大型爬行机器人进行了分类综述,依据当前深海大型爬行机器人在各方面的应用,将其分为了深海采矿机器人和深海挖沟机器人两大类,并对这两类中的一些性能突出的机器人进行了详细的介绍。重点介绍我国第一代、第二代多金属结核采矿机器人,SMD的3个多金属硫化物开采机器人,中科院深海所的富钴结壳规模采样爬行机器人,喷射式挖沟爬行机器人QT2800和机械式挖沟爬行机器人BT2400。并对深海大型爬行机器人的海底复杂行走技术和导航定位技术进行了阐述。行走技术方面,重点介绍Nexans公司的带有铰接式行走腿系统的Spider Dredger,中南大学的铰接履带式采矿机器人和北京矿冶研究总院的复合轮式机器人。导航定位方面,介绍了当前一些在用的深海导航定位技术。最后,对未来深海大型爬行机器人的发展趋势进行了展望。     

Deep-ocean piezometer probe technology for geotechnical investigations

Two single-sensor piezometer probes, 8 mm in diameter, were developed for deep-ocean geotechnical investigations. These probes were tested in a hyperbaric chamber pressurized to 55 MPa (8000 psi). Testing was performed for a period of five weeks under high hydrostatic pressure with the probes inserted in reconstituted illitic marine sediment. Small differential pore-water pressures were generated in response to both mechanically and thermally generated forcing functions. During deep-ocean simulated pressure tests, the sensors exhibited excellent sensitivity and stability. These developments in piezometer-probe technology provide a quantitative means of assessing important geotechnical parameters of fine-grained seabed deposits.     

A behavior-based approach to adaptive feature detection andfollowing with autonomous underwater vehicles

This paper presents a technique for adaptively tracking bathymetric contours using an autonomous underwater vehicle (AUV) equipped with a single altimeter sonar. An adaptive feature mapping behavior is developed to address the problem of how to locate and track features of unknown extent in an environment where a priori information is unavailable. This behavior is implemented as part of the layered control architecture used by the AUV Odyssey II. The new adaptive feature mapping behavior builds on previous work in layered control by incorporating planning and mapping capabilities that allow the vehicle to alter its trajectory online in response to sensor data in order to track contour features. New waypoints are selected by evaluating the expected utility of visiting a given location balanced against the expected cost of traveling to a particular cell. The technique is developed assuming sensor input in the form of a single, narrow-beam altimeter sensor attached to a non-holonomic, dynamically controlled survey-class AUV such as the Odyssey II. Simulations of the Charles River basin which have been constructed from real bathymetry data are used as test missions. The 7-m contour line of a prominent trench in the river serves as the target feature. The adaptive contour following behavior tracks the contour despite navigation error and environmental disturbances, supplying the capability of autonomously detecting and following distinctive bathymetric features using a point sensor. This behavior provides a foundation for future research in tracking of dynamic features in the water-column and for concurrent mapping and localization over natural terrain using a point sensor     

偏心环空螺旋流的PIV测试研究

首次将PIV技术应用于测试偏心环空幂律流体紊流螺旋流速度场,设计了一套可调偏心度的垂直环空管道实验装置。实验为不同浓度的聚丙烯酰胺水溶液在偏心度分别为40％和80％的垂直环空管道内做螺旋流动的PIV实验。得到了轴向速度影响规律：压力梯度一定时,黏滞性的减小或内管转速的增加将使轴向速度增大;流量一定时,黏滞性的减小或内管转速的增加都将使宽间隙处紊流核心区的轴向速度减小;偏心度的增大可以使紊流核心区轴向速度减小;当其它条件相同时,轴向速度随着压力梯度或流量的增加而增大。PIV实验结果与PHOENICS数模结果吻合良好。证明了PIV技术对幂律流体偏心环空螺旋流速度场进行测试是可行的、有效的。     

Control performance in the horizontal plane of a fish robot withmechanical pectoral fins

The mechanism of locomotion of aquatic animals can provide us with new insight into the maneuverability and stabilization of underwater robots. This paper focuses on biomimesis in the maneuvering performance of aquatic animals to develop a new device for maneuvering underwater robots. In this paper, guidance and control in the horizontal plane of a fish robot equipped with a pair of two-motor-driven mechanical pectoral fins on both sides of the robot in water currents is presented. The fish robot demonstrates high performance in terms of maneuverability in such activities as lateral swimming. The use of fuzzy control enables the fish robot to perform rendezvous and docking with an underwater post in water currents     

蓬莱19-3 油田事故溢油数值模拟

利用FVCOM(Finite-volume coastal ocean numerical model)数值模型和MM5风场预报模式,在对渤海海域水动力场进行数值模拟的基础上,基于"油粒子"的欧拉-拉格朗日跟踪法和随机走动原理,并考虑风对溢油油膜漂移扩散的直接作用,建立了海洋溢油油膜漂移轨迹和扩散的数值预测模型。利用建立的模型对2011年6月蓬莱19-3油田事故溢油进行了数值模拟,模拟结果与RADARSAT卫星遥感监测数据相吻合。研究结果表明:在渤海中部地区夏季事故溢油模拟预测中,风漂移因子取0.024最为合理,模型可用于渤海蓬莱19-3油田附近事故溢油轨迹和扩散的快速预报,从而为该区域的溢油事故应急响应提供科学依据。     

厦门浔江海域污染扩散数值模拟

本文采用ＡＤＩ活动边界潮流数值模拟模拟了厦门浔江海域的潮流，计算的结果与实测数据比较吻合。文中用欧拉污染扩散数值模型计算了从同安、集美、五通口排出的污染物（ＣＯＤ）对浔江海域的影响，同时采用拉格朗日污染扩散数值模型研究在湾口、集美和在北部的湾顶污染物瞬时排放后的运移情况。     

智能机器人及其发展

智能机器人是一个国家高科技发展水平的重要标志之一，具有广阔的应用前景。本文介绍了机器人的定义和发展阶段，阐述了智能机器人研究领域的关键技术，总结了国内外各类机器人的发展现状并给出相应实例，最后分析并展望了智能机器人今后的发展和研究趋势。     

基于二元LSTM神经网络的船动积分位移预测算法研究

摘要：在海况环境下,进行船舶运动预测时。由于惯性传感器采集系统本身的电学特性,会产生偏移误差,严重影响一般预测方法的准确性。针对这一问题,在常规LSTM神经网络的基础上,设计改良了一种二元的LSTM网络架构。在船舶运动仿真平台上进行模拟船舶升沉运动实验,并通过惯性传感系统测量仿真平台实时积分位移进行计算验证。验证统计该网络预测结果峰差值均方差0.64%,均值均方差0.42%,峰值均方差0.57%,证实该网络较常规LSTM在船舶运动预测领域具有更好的针对性和适应性,更准确的还原预测实际的船舶运动轨迹。     

海洋背景磁场模拟计算及东中国海表层磁场分布

海洋中海水的运动会切割地球磁场,生成微弱的电场,进而在海洋内部和周围空间激发感生电磁场,即约为地球磁场一万至十万分之一的微弱海洋背景磁场.文中针对海洋背景磁场的生成机制及近几十年来对海洋背景磁场的理论研究,结合世界磁场模型WMM2005,模拟计算了三种典型的海洋运动--海浪、海流、内波所产生的感应磁场,建立了海洋背景磁场的数值计算模型,并在此基础上设计开发了海洋背景磁场的模拟计算软件.最后用卫星多传感器资料驱动普林斯顿海洋动力学模式,得到的东中国海2005年海洋表层环流数据,模拟计算了东中国海海表层磁场分布,对其磁场变化与分布规律作了简要分析.     

An Integrated Hydrodynamics and Control Model of A Tethered Underwater Robot

An integrated hydrodynamics and control model to simulate tethered underwater robot system is proposed. The governing equation of the umbilical cable is based on a finite difference method, the hydrodynamic behaviors of the underwater robot are described by the six-degrees-of-freedom equations of motion for submarine simulations, and a controller based on the fuzzy sliding mode control (FSMC) algorithm is also incorporated. Fluid motion around the main body of moving robot with running control ducted propellers is governed by the Navier–Stokes equations and these nonlinear differential equations are solved numerically via computational fluid dynamics (CFD) technique. The hydrodynamics and control behaviors of the tethered underwater robot under certain designated trajectory and attitude control manipulation are then investigated based on the established hydrodynamics and control model. The results indicate that satisfactory control effect can be achieved and hydrodynamic behavior under the control operation can be observed with the model; much kinematic and dynamic information about tethered underwater robot system can be forecasted, including translational and angular motions of the robot, hydrodynamic loading on the robot, manipulation actions produced by the control propellers, the kinematic and dynamic behaviors of the umbilical cable. Since these hydrodynamic effects are fed into the proposed coupled model, the mutual hydrodynamic influences of different portions of the robot system as well as the hydrological factors of the undersea environment for the robot operation are incorporated in the model.     

基于径向基神经网络的水下自主航行器寻源算法研究

针对水下航行器在二维信号场中的场源搜索问题,提出了一种基于径向基函数神经网络（radial basis function neural network,简称RBFNN）的在线自主寻源算法。在神经网络中引入全局正则化参数以保证泛化性和稳定性,通过最小化广义交叉验证误差（generalized cross-validation,简称GCV）进行正则化参数的迭代优化,并利用增量式奇异值分解（incremental SVD）对迭代过程进行加速,此外通过基于样本新颖性的资源分配网络算法（resource-allocating network,简称RAN）进行径向基函数的分配,在此基础上使用动量梯度算法进行航行器运动方向的规划。最后,以热泉区硫化氢浓度分布场中的搜索作业为背景,使用该算法与其他研究中的算法进行单峰值信号场的场源搜索模拟计算对比,结果显示该算法对于信号场梯度的估计更加准确,且搜索过程的路径更短。此外在多峰值信号场的寻源模拟中该算法能够以较高的成功率通过局部最大值区域。证明该算法具有良好的拟合、预测性能以及稳定性,并且能在一定程度上避免陷入局部最优解。     

传感器优化配置的修正逐步累积法

讨论了模态实验中传感器的配置问题。利用结构振型矩阵转置的 QR分解得到传感器的初始配置。以模态置信度 MAC矩阵的最大非对角元为目标函数 ,利用本文提出的修正逐步累积法得到传感器的配置 ,并提出传感器配置必须结合优化效果和经济性 2方面综合考虑     

在狭窄通道环境下书库管理机器人的最优路径规划

研究移动机器人在狭窄通道环境下的定位和路径规划问题。首先,根据在书架和图书上预置的射频识别(RFID)标签,利用RFID技术提出了确定书库管理机器人位置和姿态的方法。然后,根据书库的书架间通道狭窄的特点,将书库管理机器人的行驶状态分解为匀速直线运动和原地匀速旋转运动,并给出了机器人匀速直线运动和原地匀速旋转运动的用时模型。最后,提出一种书库管理机器人从任意起始位置和姿态到达任意目标位置的最小用时路径规划算法。仿真结果表明,本文提出的路径规划算法是有效的。     

基于最小二乘法与RBF神经网络的溶解氧检测系统设计

为克服温度对溶解氧传感器的影响,对极谱型溶解氧检测系统的溶解氧电极激励源、高精度信号采样、软件标定和温度补偿等方面进行研究。通过对极谱型溶解氧传感器工作原理进行分析,设计了极谱型溶解氧传感器检测电路;根据溶解氧电极的温度特性,设计了基于NTC(负温度系数)热敏电阻的硬件温度补偿电路,并利用最小二乘法及RBF神经网络构建了软件温度补偿模型。利用饱和蒸馏水进行温度补偿实验,结果表明:经温度补偿后,该溶解氧检测系统的相对误差及采样波动均在1%以内,大大减小了传感器的非线性误差,测量精度和稳定性均可满足应用要求。