基于LabWindows/CVI的排水管道机器人测控系统设计

介绍了国内排水管道现状及检测与维护情况,针对排水管道机器人特殊的作业环境,设计了一种基于LabWindows/CVI的排水管道机器人测控系统。该系统以PLC为核心,采用电涡流位移传感器与摄像头结合检测管道缺陷,引入模糊控制算法,增强了系统的鲁棒性和可靠性。通过基于LabWindows/CVI虚拟仪器设计的上位机软件与下位机PLC实时通信,实现了系统对机器人动作的控制,以及数据的采集、处理、存储、显示等功能。整个系统人机交互简单、抗干扰性强、可靠性好,可满足机器人作业时的清理和检测要求。     

机械自适应管道机器人的机构原理与仿真分析

针对轮式管道机器人在遇到弯管或不规则管时会发生运动干涉的问题,提出将三轴差动轮系引入管道机器人驱动系统中,使轮式管道机器人具有对管道环境的自动适应性能,并对机械自适应管道机器人的机械结构进行了设计与研究．同时,对管道机器人进行了三维建模及运动仿真分析,验证了应用三轴差动轮系的管道机器人具有较强的弯管适应能力及管内运动的稳定性．该机器人具有适应能力强、结构紧凑、驱动效率高、工作可靠及成本低的特点．     

融合视觉和嗅觉的管道探测机器人的设计与实现

介绍了一种新型管道探测机器人系统．采用视频分划生成的十字线,对管道内的视频图像信号中的目标信号进行识别和判断;利用气体传感器对管道内残留的有害气体进行识别和判断,并融合两部分的判断结果送入控制系统,用以控制机器人的移动和对目标执行动作．本系统采用巧妙的机械结构有效实现机器人在直管和弯管进行简易、快速、准确的检测．通过原理样机验证了这套系统的可行性．     

基于单目视觉的水下机器人管道检测

以单目CCD摄像机为视觉传感器,利用视觉系统测量方法获得水下管道的导航信息,并在此基础上建立了一个用于水下机器人的水下管道检测系统． 按照数据结构的抽象程度,将系统中传递的数据信息分为由低至高4个层次,描述了各层次内容,详细介绍了水下机器人管道检测方法． 为了提高系统的准确性和实时性,采用了动态窗口管道检测方法．在室内实验水池中,以某型号水下机器人为试验载体,进行了多次管道跟踪试验,验证了系统的可行性和有效性．     

渗滤液导排管道检测机器人的研究

针对垃圾填埋场渗滤液导排管道检测的需要,研究了一种基于CCD摄像方法的管道检测机器人系统,该系统主要由机器人的驱动装置、预清洗装置、检测系统、控制系统和地面工作站等组成.详细介绍了管道检测机器人的系统总体设计和各组成部分的功能.经系统测试和现场实验表明,该系统能够在管道内平稳运行、传输出清晰地管道内壁图像、完成管道清洗的工作,实现管道机器人的远程信息的交换和控制.     

城市燃气管道检测机器人测控系统研究与发展现状

检测与控制系统分别用于城市燃气管道检测机器人在管道内的缺陷检测和运动控制,是城市燃气管道检测机器人核心部分.综述了国内外城市燃气管道检测机器人测控系统研究和发展现状;论述了城市燃气管道检测机器人测控系统发展过程;结合各种燃气管道检测机器人系统构成示意图及测控系统构架图,阐述了测控系统工作原理,重点分析了基于通信线缆通信和基于无线通信的监督式测控系统;指出了未来城市燃气管道检测机器人测控系统的研究方向.     

多模块蛇形管道打磨机器人的设计与分析

设计了一种由多个模块构成的蛇形管道打磨机器人,各个模块之间可以快速拆装,其中驱动模块为机器人在管道中前行提供动力牵引．该机器人可以主动适应内径为250 mm~450 mm的直管道、弯管道及其组合管道,可以在管道内部实现以打磨作业为主的作业功能．同时,提出了适用于蛇形管道打磨机器人自身过弯管的速度模型,通过对机器人的力学分析得出各个模块之间相互作用力的计算方法及影响机器人在管道内部转体运动发生的因素．在ADAMS软件中进行了虚拟样机仿真验证,初步验证了蛇形管道打磨机器人的通过性并得出机器人在管道内部前行的最佳匹配．最后,搭建了实验平台,制作了机器人真实样机,验证了机器人对内径为250 mm~450 mm管道的适应性、通过性及作业效果．     

三轴差动式管道机器人驱动单元自适应特性实验研究

为验证三轴差动式管道机器人驱动单元机械自适应特性,深层解析三轴差动式驱动单元的机构传动原 理,研制了包含三轴差动驱动单元、模拟运行环境、性能测试系统在内的机器人自适应特性实验系统．以定量评价 三轴差动驱动单元特性为目标,建立了性能指标评价集,客观评价了新型三轴差动驱动单元的性能．实验研究表明, 三轴差动式管道机器人驱动单元对管道环境的几何约束的各种变化具有良好的机械自适应特性．     

关节式带电清扫机器人的绝缘性及安全性设计

关节式带电清扫机器人（简称“HVCR II”）是一种遥操作机器人,用于330kV变电所高压设备外绝缘瓷瓶的带电清扫．本文介绍了其在绝缘性和安全性设计上的一些研究工作,包括绝缘结构设计、绝缘操作方式、控制系统以及泄漏电流实时监测及报警系统的设计．工频耐压试验和模拟带电清扫试验表明,关节式带电清扫机器人有良好的绝缘性能,并具备了明朗的应用前景．     

油田抽油泵泵筒内表面激光改性机器人的研制

本文介绍了油田泵筒内表面激光改性机器人系统的 结构及工作原理．该技术将激光表面改性技术和管道机器人技术相结合，具有功能完善、可 靠性高、可控制性好、成本低等优点．实验证明,是进行管材内表面激光淬火的一种新的有 效方法，在工程应用中具有推广价值．     

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.     

用于避障研究的微型仿生机器鱼3维仿真系统

基于VC++6.0开发环境和OpenGL（open graphics library）国际图形标准,在Windows系统下开发了微型仿生机器鱼3维仿真系统。该系统可以降低用实体机器鱼进行机器鱼避障能力研究的成本和减少在研究过程中对实体机器鱼造成的损害。采用多边形建模的方法构建了虚拟微型仿生机器鱼模型,模拟了鱼类尾鳍的摆动。提出了一种模拟红外传感器探测障碍物的虚拟射线方法。并采用实时模糊决策算法设计了基于多传感器信息的复合模糊控制器,决策微型仿生机器鱼的避障行为。仿真实验表明,复合模糊控制器实时性好、效率高;无论是单个任意形状的障碍物还是多个连续障碍物,复合模糊控制器都能有效地引导仿生机器鱼避开障碍物,到达目标点。微型仿生机器鱼3维仿真系统为研究仿生机器鱼的自主避障能力提供了可靠、逼真、便利的平台。     

Design and manufacturing of mobile micro manipulation system with a compliant piezoelectric actuator based micro gripper

This paper presents a new design of mobile micro manipulation system for robotic micro assembly where a compliant piezoelectric actuator based micro gripper is designed for handling the miniature parts and compensation of misalignment during peg-in-hole assembly is done because piezoelectric actuator has capability of producing the displacement in micron range and generates high force instantaneously. This adjusts the misalignment of peg during robotic micro assembly. The throughput/speed of mobile micro manipulation system is found for picking and placing the peg from one hole to next hole position. An analysis of piezoelectric actuator based micro gripper has been carried out where voltage is controlled through a proportional-derivative (PD) controller. By developing a prototype, it is demonstrated that compliant piezoelectric actuator based micro gripper is capable of handling the peg-in-hole assembly task in a mobile micro manipulation system.     

Signal processing and defect analysis of pipeline inspection applying magnetic flux leakage methods

Corrosion, stresses and mechanical damage of oil and gas pipelines can result in catastrophic failures, so pipeline safety evaluation is an important problem of oil and gas transmission. To evaluate the pipeline safety, this paper described a novel magnetic flux leakage (MFL) inspection device, and the designing MFL intelligent inspection pig was used to multi-radius pipelines and variational work condition. At the same time, because signal processing and defect recognition technique is one of the most important techniques in offshore pipeline inspection MFL system, the paper also discussed its signal processing procedure. Time-frequency analysis, median and adaptive filter, and interpolation processing are adopted to preprocess MFL inspection signal. In order to obtain high sensitivity and precision, we adopted multi-sensor data fusion technique. A wavelet basis function neural network was used to recognize defect parameters. The main contribution of the article is that we presented a novel method to evaluate and predict oil pipelines’ condition through combining neural network, data fusion and expert system techniques, and through constructing a knowledge-based off-line inspection expert system, the system improved its defect recognition capability greatly.     

埋地管道检测技术现状与展望

定期对埋地管道进行检测有利于管道的维护管理和完整性评价。对埋地管道常用的外检测和内检测技术进行了综述,包括用于管道缺陷检测的超声检测、涡流检测、漏磁检测和视觉检测,以及用于管道变形检测的通径检测法、超声波法、激光三角法、环形光投射成像法等。阐述了各检测方法的基本原理,总结了各自的优势与局限性,为检测技术的选择提供了有效参考。梳理了埋地管道检测技术的发展现状,特别是电磁超声、漏磁、视觉内检测技术的新进展,分析了管道检测的发展趋势,并给出了一些技术难点的解决思路。目前的研究热点表明,埋地管道检测技术正在朝着复杂化对象的检测新方法、缺陷定量化、检测数据可视化的方向发展。     

Autonomous robotic inspection and manipulation using multisensorfeedback

A six-degree-of-freedom industrial robot to which was added a number of sensors-vision, range, sound, proximity, force/torque, and touch-to enhance its inspection and manipulation capabilities is described. The work falls under the scope of partial autonomy. In teleoperation mode, the human operator prepares the robotic system to perform the desired task. Using its sensory cues, the system maps the workspace and performs its operations in a fully autonomous mode. Finally, the system reports back to the human operator on the success or failure of the task and resumes its teleoperation mode. The feasibility of realistic autonomous robotic inspection and manipulation tasks using multisensory information cues is demonstrated. The focus is on the estimation of the three-dimensional position and orientation of the task panel and the use of other nonvision sensors for valve manipulation. The experiment illustrates the need for multisensory information to accomplish complex, autonomous robotic inspection and manipulation tasks     

A robotic system for internal inspection of water pipelines

This research has been motivated by the need for a reliable, robust, and cost-effective tool for internal pipe inspection with application to preventive and predictive maintenance. A new design for a visual inspection system for the interior of water pipelines with minimal service interruption is presented. The method proposed is especially designed to work in the in-water environment. We first describe water pipelines and the challenges of navigation in their interior, and the current practices for failure detection are presented. We also present the mechanical design, the electronics and communication systems, the fiber-optic bus, and the operator station. Two image-processing algorithms for measuring fissure length and the effective diameter of the pipe are also presented, including examples of operation on real pipelines     

Development of an autonomous bridge deck inspection robotic system

The threat to safety of aging bridges has been recognized as a critical concern to the general public due to the poor condition of many bridges in the United States. Currently, the bridge inspection is conducted manually, and it is not efficient to identify bridge condition deterioration in order to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report a new development of the autonomous mobile robotic system for bridge deck inspection and evaluation. The robot is integrated with several nondestructive evaluation (NDE) sensors and a navigation control algorithm to allow it to accurately and autonomously maneuver on the bridge deck to collect visual images and conduct NDE measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection and inspection. For efficient bridge deck monitoring, the crack detection algorithm to build the deck crack map is presented in detail. The impact‐echo (IE), ultrasonic surface waves (USW), and electrical resistivity (ER) data collected by the robot are analyzed to generate the delamination, concrete elastic modulus, corrosion maps of the bridge deck, respectively. The presented robotic system has been successfully deployed to inspect numerous bridges in more than ten different states in the United States.     

Vision-Based Robotic Motion Control for Non-autonomous Environment

A visual servo control system with SOPC structure is implemented on a retrofitted Mitsubishi Movemaster RV-M2 robotic system. The hardware circuit has the functions of quadrature encoder decoding, limit switch detecting, pulse width modulation (PWM) generating and CMOS image signal capturing. The software embedded in Nios II micro processor has the functions of using UART to communicate with PC, robotic inverse kinematics calculation, robotic motion control schemes, digital image processing and gobang game AI algorithms. The digital hardware circuits are designed by using Verilog language, and programs in Nios II micro processor are coded with C language. An Altera Statrix II EP2S60F672C5Es FPGA chip is adopted as the main CPU of the development board. A CMOS color image sensor with 356 ×292 pixels resolution is selected to catch the environment time-varying change for robotic vision-based servo control. The system performance is evaluated by experimental tests. A gobang game is planned to reveal the visual servo robotic motion control objective in non-autonomous environment. Here, a model-free intelligent self-organizing fuzzy control strategy is employed to design the robotic joint controller. A vision based trajectory planning algorithm is designed to calculate the desired angular positions or trajectory on-line of each robotic joint. The experimental results show that this visual servo control robot has reliable control actions.     

Aerial robotic contact-based inspection: planning and control

The challenge of aerial robotic contact-based inspection is the driving motivation of this paper. The problem is approached on both levels of control and path-planning by introducing algorithms and control laws that ensure optimal inspection through contact and controlled aerial robotic physical interaction. Regarding the flight and physical interaction stabilization, a hybrid model predictive control framework is proposed, based on which a typical quadrotor becomes capable of stable and active interaction, accurate trajectory tracking on environmental surfaces as well as force control. Convex optimization techniques enabled the explicit computation of such a controller which accounts for the dynamics in free-flight as well as during physical interaction, ensures the global stability of the hybrid system and provides optimal responses while respecting the physical limitations of the vehicle. Further augmentation of this scheme, allowed the incorporation of a last-resort obstacle avoidance mechanism at the control level. Relying on such a control law, a contact-based inspection planner was developed which computes the optimal route within a given set of inspection points while avoiding any obstacles or other no-fly zones on the environmental surface. Extensive experimental studies that included complex “aerial-writing” tasks, interaction with non-planar and textured surfaces, execution of multiple inspection operations and obstacle avoidance maneuvers, indicate the efficiency of the proposed methods and the potential capabilities of aerial robotic inspection through contact.