Development of dam inspection robot with negative pressure effect plate

This paper describes the development of an underwater robot that performs visual inspection while making mechanical contact with a dam surface by a pulling force generated from thrusters with negative pressure effect plates. In general, small and lightweight remotely operated vehicles (ROVs) have low‐power thrusters. Their positioning performance is inferior with respect to external disturbances. Moreover, it is difficult for untrained operators to control the ROV position to check and inspect dams visually. A negative pressure effect plate attached to a thruster produces negative pressure that maintains mechanical contact between the robot and a dam wall surface and ensures stable robot motion on a dam surface to acquire clear continuous images. As described herein, we theoretically investigate the negative pressure effect plate characteristics and experimentally measure the force generated by the pressure difference. Results show that the force of a thruster with the effect plate is five times greater than the nominal thrust force provided by the thruster alone. Based on those results, we designed and developed the underwater robot with the negative pressure effect plates for dam inspection. Moreover, we conducted an experiment in a water tank and a field test at Shorenji Dam, Mie‐prefecture, Japan. The experimentally obtained results indicated that the negative pressure effective plate is effective at generating sufficient force and at realizing stable robot motion on the dam surface. Results demonstrate that the developed robot acquired clear images of the dam surface continuously with no sophisticated operator or controller.     

ROV模糊控制导航方法

本文提出一种水下ROV(Remotely Operated Vehicles)的模糊导航方法和基于该方 法的控制器结构．通常由于水下环境光照不足或是水质混浊，很难依赖摄像机准确地为ROV 导航，引导ROV到达预定目标，尤其是工作空间存在障碍物时，ROV很可能发生碰撞．文中提 出的模糊控制方法，将ROV在3D空间运动的状态、局部环境信息以及导航规划数据表示为多 重模糊条件，然后结合ROV的导航特点，建立了一个三级模糊控制器，该控制器使用同一种 控制模式完成ROV有障碍和无障碍的导航任务．仿真实验结果验证了所提出方法的有效性．     

遥控水下机器人系统在水库大坝水下检查中的应用

通过遥控水下机器人系统在水库大坝面板趾板、水库进水口、宋代古陂等工程水下检查中的实际应用,总结遥控水下机器人在清水环境下渗漏点查找、浊水环境水下冲刷检查、流动水环境水下金属锈蚀检查、易缠绕环境条件下水下检查的应用技巧,归纳遥控水下机器人系统的特点、技术优势及适用范围,为解决遥控水下机器人系统应用中出现的线缆易缠绕及难以发现大坝渗漏点等问题积累经验。     

A vision system for an underwater cable tracker

Nowadays, the surveillance and inspection of underwater installations, such as power and telecommunication cables and pipelines, is carried out by operators that, being on the surface, drive a remotely operated vehicle (ROV) with cameras mounted over it. This is a tedious and high time-consuming task, easily prone to errors mainly because of loss of attention or fatigue of the human operator. Besides, the complexity of the task is increased by the lack of quality of typical seabed images, which are mainly characterised by blurring, non-uniform illumination, lack of contrast and instability in the vehicle motion. In this study, the development of a vision system guiding an autonomous underwater vehicle (AUV) able to detect and track automatically an underwater power cable laid on the seabed is the main concern. The vision system that is proposed tracks the cable with an average success rate above 90%. The system has been tested using sequences coming from a video tape obtained in several tracking sessions of various real cables with a ROV driven from the surface. These cables were installed several years ago, so that the images do not present highly contrasted cables over a sandy seabed; on the contrary, these cables are partially covered in algae or sand, and are surrounded by other algae and rocks, thus making the sequences highly realistic. Accepted: 13 August 2001     

Nondestructive evaluation sensor fusion with autonomous robotic system for civil infrastructure inspection

Civil infrastructure inspection is crucial to maintaining the quality of that infrastructure, which has a great impact on the economy. Performing this inspection is costly work that requires workers to be trained on how to use varying technologies, which can be error prone when performed manually and can result in damage to the infrastructure in some cases. For this reason, nondestructive evaluation (NDE) sensors are preferred for civil infrastructure inspection as they can perform the necessary inspection without damaging the infrastructure. In this paper, we develop a fully autonomous robotic system capable of real‐time data collection and quasi‐real‐time data processing. The robotic system is equipped with several NDE sensors that allow for a sensor fusion method to be developed that successfully minimizes inspection time while performing adequate inspection of areas that require more in‐depth data to be collected. A detailed discussion of the inspection framework developed for this robotic system, and the dual navigation modes for both indoor and outdoor autonomous navigation is presented. The developed robotic system is deployed to inspect several infrastructures (e.g., parking garages, bridges) at and near by the University of Nevada, Reno campus.     

基于移动互联网的小型水库大坝安全巡查系统应用及研究

广东省小型水库数量众多、分散、管理难度大的特点给水利部门的管理工作带来诸多不便,而水库大坝现场巡查是大坝安全管理不可或缺、极为重要的环节。基于移动互联网和GIS技术,结合"一个登录门户,分级权限管理"的设计思想,以信息采集层、网络传输层、资源共享层、综合业务应用层的架构设计小型水库大坝安全巡查系统,分别介绍系统中的采用Java EE开发的水库大坝巡查管理平台,以及基于Android/iOS的移动巡查终端的业务流程、功能实现等内容。该系统能够明确水库大坝的巡查部位、频次和路线,规范巡查行为,进一步提升水库大坝安全管理标准化、专业化水平。     

基于VxWorks的水下机器人通信系统设计

针对水下机器人（ROV）在深海高噪声干扰环境中工作的特点,设计了一套基于VxWorks实时操作系统的ROV整体通信系统,实现了水下核心控制器对水下分系统快速高效的信息采集和数据分配,水下系统和水面控制器稳定实时的数据交换;硬件方面设计了以CAN总线为基础的水下通信系统,通过FPGA实现了CAN总线和PC104总线之间的时序逻辑转换,软件方面设计了基于TCP/IP协议栈的水面操控台和ROV之间的网络通信方式和水下各系统之间的CAN总线通信方式,着重介绍了基于缓冲队列的网络通信编程;通信系统数据测试实验表明：CAN总线通信和网络通信均具有良好的实时性和可靠性,满足最初的设计需求,而且采用模块化设计,便于维护和移植。     

水下狭窄环境中ROV的自主返回控制

为满足缆控水下机器人（remotely operated vehicle,ROV）在水下狭窄环境中作业完毕后的顺利回收需求,研究仿真ROV的路径跟踪以及动力定位系统。基于非对称ROV构建数学模型,利用李雅普诺夫函数,采用反向递推和反馈线性化,设计了基于反步法的自适应控制器。该控制器通过反馈线性化,将已知非线性参数转化成线性参数,不确定的非线性参数应用自适应控制律进行放宽。通过仿真对该控制器应用于ROV的可行性进行验证表明:基于反步自适应控制以及视线导引的算法,ROV在水下狭窄环境中路径跟踪效果良好,动力定位稳定,鲁棒性良好,能够很好地解决ROV模型的不确定性与非线性问题。该控制器为ROV在水下狭窄环境中的回收作业提供了很好的解决方案。     

Underwater inspection of bridge substructures using sonar and deep convolutional network

Bridges are vital structures for worldwide physical infrastructure networks, and efficient inspection methods are needed to reveal and evaluate the health conditions of damaged critical bridges. In contrast to the superstructure inspection, underwater inspection methods are still time-consuming and labor-intensive tasks. As the underwater environment is invisible and hard to access, scouring and damage are easily neglected in traditional human diving. To address this problem, this paper presents a rapid underwater inspection framework using a sonar device and a deep convolutional network to provide quantitative measuring results for scour depth and apparent damage. The side-scan sonar and fixing platform were used to collect underwater images, and a modified semantic segmentation was designed based on the U-Net architecture. The pretrained residual building blocks and a designed feature fusion connection called Respath were utilized to replace the original encoder and skip connection. Comparative experiments showed that this modified architecture achieved the best performance in multiple-class segmentation for sonar images in which the mean intersection over union (mIoU) and IoU for specific apparent damage can reach up to 0.918 and 0.63, respectively. An on-site test was also conducted to validate the applicability of the proposed method, and the scour depth and two points of damage were identified based on the pixelwise segmentation images. Therefore, further structural evaluation can proceed based on these accurate measuring results.     

基于LabVIEW的透镜多参数自动检测系统开发

质量检测是光学透镜生产的重要环节,目前大部分透镜生产企业还停留在半自动检测阶段,质检的效率和精度很大程度上取决于工人的熟练程度;且不同参数的检测需要人工搬运镜片到不同的质检工位上,质检过程中的反复搬运容易造成镜片表面污染和损伤;为此提出一种基于LabVIEW的透镜多参数自动检测系统的设计方法,在一个工位上同时完成多个质量参数的测量,并对透镜进行自动搬运和分选,检测结束后自动生成质检报表;最后使用某型号凸型圆形透镜对开发的检测系统进行了实验验证,实验结果表明,检测系统具有测量精度高、可扩展能力强、界面直观等优点。     

Combined depth and heading control and experiment of ROV under the influence of residual buoyancy,current disturbance,and control dead zone

To improve the underwater control effect of a Remotely Operated Vehicle (ROV) with residual buoyancy, current disturbance, and control dead zone, the depth and heading combined control of ROV is studied to improve the control accuracy of the control system. First, the heading control with fixed depth is divided into heading control and depth control. The tanh-sigmoid-surface control laws for designed degrees of freedom are designed by using tanh function. To suppress the influence of residual buoyancy and control law dead zone in depth control, and to offset the influence of control law dead zone of ROV thruster control, a reserved control quantity is introduced to map the depth deviation and control dead zone with residual buoyancy into a control deviation quantity. An adaptive amplification factor method is proposed for the amplification factors of depth control, speed control, and heading control. The proportional coefficient is adopted to make that the balance among rise time, convergence speed, and overshoot can be achieved by adjusting the proportional coefficient. Then the corresponding tanh-sigmoid-surface controller module is designed in MOOS-IvP environment to track the desired heading and depth. The proposed controller refines fuzzy rules and reduces the complexity of parameter adjustment. Compared with the classical proportional, integral, and derivative control method, the experiment results show that the proposed method can resist the influence of residual buoyancy, current disturbance, and control dead zone and has a better control effect with less control error in depth and heading determination.     

基于立体视觉的水下三维测量系统研究

随着我国海洋战略的提出,对于海洋观测技术和装备的需求日趋迫切。针对现有水下成像系统无法实现精确三维测量这一难题,该文提出了一种基于双目立体视觉原理的水下三维测量系统研究方法,并对其可行性进行了验证。针对水下成像过程存在的水体界面折射问题,该文提出了相应的相机成像模型及系统参数标定方法,建立了防水深度达 30 m 的双目水下测量及照明装置,并在水池、近海条件下进行了实地测试。实验结果显示,在水体条件较好的情况下,系统观测距离可达 8 m 以上,有效测量距离为 0.5～4.5 m,在 0.5 m 和 4.5 m 距离处的测量误差分别为 2 mm 和 20 mm。实验验证了 水下双目成像模型、立体标定、测量模型等方法的有效性和精确性,可为水下检修作业等海洋工程行业提供一种有效的三维测量技术手段。     

A particle filter-based approach for tracking undersea narrow telecommunication cables

The surveillance and inspection of underwater installations such as telecommunication cables are currently carried out by trained operators who, from the surface, guide a remotely operated vehicle (ROV) with cameras mounted over it. This manual visual control is, however, a very tedious job that tends to fail if the operator loses concentration. This paper describes a tracking system for underwater narrow telecommunication cables, the main objective of which is to allow an autonomous underwater vehicle to video-document the whole length of a cable. The approach is based on particle filters (PFs) because of their natural ability to model multi-dimensional multi-modal PDFs, which allows handling in a more appropriate way the ambiguities that naturally arise from undersea environments. In effect, despite the special visual features that artificial objects present, which allow distinguishing them in natural scenarios such as the seabed, distracting background such as rocks or algae growing on top and nearby cables, complicate the detection and tracking and give rise to ambiguities when rocks or marine growth form shapes and textures that resemble the cable. Apart from the different models that a PF requires, the paper also describes a set of added features, which successfully compensate some large errors in the cable pose estimation when the non-enhanced tracker is applied. Extensive experimental results over a test set of more than 10,000 frames, for which a ground truth has been manually generated, have shown the usefulness of the solution proposed. Besides, results for a set of six video sequences accounting for almost 150,000 frames and around one hour and a half of successful continuous video tracking are also discussed. All those images come from inspection runs captured by ROVs navigating over real telecommunication undersea cables.     

水下机器人递阶－分散式控制系统研究

本文给出了水下机器人（ＲＯＶ）的一种递阶－分散式计算机控制系统。通过计算机硬件和软件的并行处理技术，解决了ＲＯＶ控制的实现问题。实际应用表明，该系统具有结构简单，运算速度快等特点．     

改进YOLOv3-SPP水下目标检测研究

针对水下目标检测任务中图像模糊、背景复杂以及目标小而导致误检和漏检问题,提出一种改进YOLOv3-SPP的水下目标检测算法。利用UWGAN网络对水下原始图像进行恢复,采用Mixup方法增强数据,减少错误标签记忆;以YOLOv3-SPP网络结构为基础,增加网络预测尺度,提高小目标检测性能;引入CIoU边框回归损失,提高定位精度;利用K-Means++聚类算法,筛选最佳Anchor box。将改进YOLOv3-SPP算法在处理后的URPC数据集上进行实验,平均检测精度由79.58%提升到88.71%,速度为28.9 FPS。结果表明,改进算法综合检测能力优于其他算法。     

遥控水下机器人（ROV）分布式控制系统

本文阐述了我国自行研制的６００ｍ水深作业型缆控水下机器人（ＲＯＶ）Ｂｉｔｂｕｓ（位总线）分布式控制系统的硬件结构和软件体系。     

供电服务督检现场检查仪优化设计研究

针对传统供电服务督检现场检查仪优化方法缺少对数据的分类融合处理,导致方法准确性较差的问题,提出基于大数据信息融合和物联网组网节点的供电服务督检现场检查仪优化设计,采用传感器融合识别方法,实现供电服务督检现场检查仪的大数据采集,通过对采集大数据的关联规则特征挖掘和信息识别,提取检查信息的关联特征量,采用物联网技术实现信息的分类检测和信息融合处理,基于嵌入式的物联网组网技术设计供电服务督检现场检查系统,结合模糊控制方法,实现供电服务督检现场检查仪优化设计,提高供电服务督检现场检查的自动化水平。仿真测试结果表明,采用该方法能有效检测到电压或电流谐波含量,检测有效性为97.65%,证明所提方法供电服务督检现场检查的智能性较好,能够应用在供电服务督检现场检查仪中,更好地实现供电服务督检现场检查仪的优化。     

Sea floor geometry approximation and altitude control of ROVs

This paper presents a method for sea floor geometry approximation in a local region beneath a remotely operated vehicle (ROV) for use in altitude control. The method is based on Doppler velocity log (DVL) altitude measurements and ROV state estimates. The ROV altitude and sea floor gradient, which are obtained from the sea floor approximation, are used in a guidance law for altitude control. The altitude observer and guidance law have been implemented in the control system of NTNU׳s ROV Minerva. Results from simulations and sea trials demonstrating the performance of the proposed altitude estimation and guidance system are presented in the paper.     

Analysis of Dynamic Characteristics of Water Hydraulic Rotating Angle Self-Servo Robot Joint Actuator

The application of robots as a tool to explore underwater environments has increased in the last decade. Underwater tasks such as inspection, maintenance, and monitoring can be automatized by robots. The understanding of the underwater environments and the object recognition are required features that are becoming a critical issue for these systems. On this work, a method to provide a semantic mapping on the underwater environment is provided. This novel system is independent of the water turbidity and uses acoustic images acquired by Forward-Looking Sonar (FLS). The proposed method efficiently segments and classifies the structures in the scene using geometric information of the recognized objects. Therefore, a semantic map of the scene is created, which allows the robot to describe its environment according to high-level semantic features. Finally, the proposal is evaluated in a real dataset acquired by an underwater vehicle in a marina area. Experimental results demonstrate the robustness and accuracy of the method described in this paper.     

Docking at pool and sea by using active marker in turbid and day/night environment

Nowadays, autonomous underwater vehicle (AUV) is playing an important role in human society in different applications such as inspection of underwater structures (dams, bridges). It has been desired to develop AUVs that can work in a sea with a long period of time for the purpose of retrieving methane hydrate, or rare metal, and so on. To achieve such AUVs, the automatic recharging capability of AUVs under the sea is indispensable and it requires AUVs to dock itself to recharging station autonomously. Therefore, we have developed a stereo-vision-based docking methodology for underwater battery recharging to enable the AUV to continue operations without returning surface vehicle for recharging. Since underwater battery recharging units are supposed to be installed in a deep sea, the deep-sea docking experiments cannot avoid turbidity and low-light environment. In this study, the proposed system with a newly designed active—meaning self-lighting—3D marker has been developed to improve the visibility of the marker from an underwater vehicle, especially in turbid water. Experiments to verify the robustness of the proposed docking approach have been conducted in a simulated pool where the lighting conditions change from day to night. Furthermore, sea docking experiment has also been executed to verify the practicality of the active marker. The experimental results have confirmed the effectiveness of the proposed docking system against turbidity and illumination variation.