智能检测行业机器视觉开发套件设计

当前国内市场对于视觉检测的需求巨大，但是国外检测软件在中国的市场占有率高达90%，且授权把控非常严格，拥有绝对的市场优势和话语权，使得我国在工业检测方面长期面临“卡脖子”困境。基于此，自主研发机器视觉开发套件。通过软件架构设计、核心功能模块开发、图形化人机编程、多相机管理等技术开发，建立丰富的函数库和子程序集，实现无代码编程，用户可轻松进行二次开发。基于该软件平台，根据不同行业需求，可开发出不同应用的工业检测软件。该机器视觉开发套件的研究对打破国外技术垄断，建立与硬件执行平台相配套的工程学习、开发平台具有重要的作用和意义，有利于推动我国工业生产智能化的快速发展。     

变电站应用智能机器视觉的探索

为了应对变电站智能化的趋势,使用机器视觉检测技术对现有变电站进行智能化改造与升级。使用数字无线摄像头、机器人移动平台、WIFI数据链网络、高性能工业计算机和手持个人终端,组成了变电站的智能监控系统。该系统能够实现防走错间隔、接地线统一管理、巡视机器人引导等功能。     

基于开源操作系统ROS的机器人软件开发

ROS(机器人操作系统)是一套机器人软件框架,基于这一框架,人们可以快速开发出控制机器人的一系列应用,是目前大多数机器人系统的首选软件平台.扫地机器人、四轴飞行器、机器小车等,虽然各自的配件、外形或功能等各不相同,但是它们有一个共同点就是均运行在ROS系统框架之上.ROS本身的优良设计使其兼具了精简与集成、多语言多平台支持、点对点设计以及开源免费等特点.目前,越来越多的机器人厂商将基于ROS平台进行软件设计研发,而更多厂商的使用反过来又成为ROS的进一步完善与普及的巨大推动力.     

基于云端服务资源的室内外连续监控机器人系统架构设计

针对传统移动监控方式智能化程度低造成操控难度和工作强度大以及本地数据管理困难的问题,面向业界对室内外移动平台统一性的迫切需求,提出了一种云端服务资源和本地自主机器人结合的系统架构。首先,给出系统结构,包括：1）为系统提供自主行为能力的自主移动机器人端,实现室内/外无缝导航、图像/视频推送等;2）提供人机和远程交互的远程监控端;3）为室内/外运行提供统一数据传输和管理通路的云数据服务边。然后,对系统进行任务架构设计,根据监控数据传输特点,采用两套商用云平台实施云数据处理任务,并为两端子系统设计了带有云交互功能的任务栈。在此基础上,结合多项云服务设计了系统软件架构。最后,采用“上下位机-协处理器-功能模块”方式设计实现自主移动机器人端硬件系统,基于机器人操作系统（ROS）节点模型构建该端软件系统;远程监控端上,主要设计图形用户界面和信息交互逻辑。实验结果表明,所设计系统仅需少量控制指令便可远距离实现室内、外环境的连续监控,且操控工作强度被有效降低,压力测试中系统指令往返时延一般不超过160 ms,多时段测试中视频码率不低于1 Mb/s,均表明系统具备应用实时性和可靠性。     

基于ROS网桥的跨平台网络化人机交互系统设计

针对传统机器人控制系统存在的跨平台开发和部署问题，提出了一种基于ROS(Robot Operating System,机器人操作系统)网桥的跨平台网络化人机交互系统。构建以Node.js框架为服务后端，Bootstrap框架和jQuery组件为交互前端的网络化控制系统架构，通过ROS网桥技术实现万维网(World Wide Web, WWW)端和机器人端的跨平台数据互通，并按需进行机器人控制服务化调用。实验结果表明，该控制系统能够实现机器人端环境感知、状态监视、远程控制等功能，支持个人电脑(Personal Computer, PC)端、移动端等泛平台人机交互，具有可模块化敏捷开发、移植扩展性强等优点。     

输电线路巡检机器人远程测控系统的研究与实现

开发了一种针对输电线路巡检机器人的新型远程测控系统.该系统通过与机器人本地控制器的实时通信和多线程技术实现机器人姿态监控和机器视觉检测.通过对机器人控制器发送命令和接收数据实现对机器人的人工遥操作;采用Matlab Script节点实现Matlab与LabVIEW混合编程,完成机器人质心和多关节姿态的计算,采用共享数据库方式调用基于Visual Prolog开发的机器人行为规划应用程序,实现机器人姿态自主控制.实验结果表明,该远程测控系统运行可靠,实时性强,具有良好的人机交互能力.     

基于FPGA的机器人视觉系统研究与设计

本文在研究现有机器人视觉系统功能、原理、结构和实现方法基础上,完成了以FPGA(Field Programmable Gate Array,现场可编程门阵列)和COMS图像传感器为核心平台的视觉系统硬件设计,以硬件描述语言为工具完成了常见数字图像处理算法实现,完成了人脸识别系统的应用开发。较传统机器视觉硬件系统而言,基于FPGA的机器人视觉系统具有体积小、功耗低、速度快、配置灵活、移植方便等突出优点,可广泛应用于对响应速度要求高、定制化服务需求的机器人视觉系统中,提高系统设计效率。     

基于角偏移控制算法的机器人伺服寻迹系统设计

机器视觉和嵌入式系统是机器人领域研究的热点。随着计算机技术的发展,机器视觉在工农业生产和国防等领域已得到成功的应用。本文将机器视觉和嵌入式系统综合用于竞赛机器人的运动控制,构建一个嵌入式机器人视觉伺服寻迹系统的平台,完成相关的硬件和软件设计及制作。设计制作的试验平台能够动态地获取、处理和分析视频图像数据,将分析结果反馈于机器人本体驱动电机,实现机器人本体的自主动态寻迹,且其误差精度能得到很好的保证。     

机器人大赛中的物联网感知和机器视觉的应用

通过物联网传感器和数据分析技术,机器人可以获得更广泛的态势感知,从而更好地执行任务。文中根据机器人大赛动态避障赛程的集体要求,搭建了基于ROS平台工业机器人开源平台,应用Python语言进行Gazebo虚拟现实系统的搭建,基于双目视觉完成了静态避障与动态避障功能,完成了机器人大赛的具体比赛。     

基于ROS的移动机器人平台系统设计

ROS是一个开源机器人操作系统。通过对机器人操作系统的研究,首先介绍了ROS系统框架和结构特点,其次提出了在ROS环境下搭建移动机器人平台的方法,并介绍了移动机器人系统的硬件平台,最后阐述了移动机器人各个功能模块。该移动机器人可以根据事先确定的任务自主进行全局路径规划,同时不断感知周围的局部环境信息,对ROS的应用有着重要的意义。     

嵌入式智能机器人平台研究

针对传统工业机器人采用的封闭式结构的局限性,在Windows CE.NET系统基础上,通过剪裁定制,去除冗余的功能,搭建嵌入式智能机器人平台．该智能机器人系统具有移动机器人需要的主要感知模块,并有丰富的运动控制接口及驱动模块．同时,设计了多传感器数据融合、轨迹规划、运动控制、无线网络通信、图形人机界面等智能机器人的测试软件和应用模块．该智能机器人平台具有模块化、易扩展、可移植、可定制、硬件体积小、功耗低、实时性强、可靠性高等优点．     

An affordable modular mobile robotic platform with fuzzy logic control and evolutionary artificial neural networks

Autonomous robotics projects encompass the rich nature of integrated systems that includes mechanical, electrical, and computational software components. The availability of smaller and cheaper hardware components has helped make possible a new dimension in operational autonomy. This paper describes a mobile robotic platform consisting of several integrated modules including a laptop computer that serves as the main control module, microcontroller‐based motion control module, a vision processing module, a sensor interface module, and a navigation module. The laptop computer module contains the main software development environment with a user interface to access and control all other modules. Programming language independence is achieved by using standard input/output computer interfaces including RS‐232 serial port, USB, networking, audio input and output, and parallel port devices. However, with the same hardware technology available to all, the distinguishing factor in most cases for intelligent systems becomes the software design. The software for autonomous robots must intelligently control the hardware so that it functions in unstructured, dynamic, and uncertain environments while maintaining an autonomous adaptability. This paper describes how we introduced fuzzy logic control to one robot platform in order to solve the 2003 Intelligent Ground Vehicle Competition (IGVC) Autonomous Challenge problem. This paper also describes the introduction of hybrid software design that utilizes Fuzzy Evolutionary Artificial Neural Network techniques. In this design, rather than using a control program that is directly coded, the robot's artificial neural net is first trained with a training data set using evolutionary optimization techniques to adjust weight values between neurons. The trained neural network with a weight average defuzzification method was able to make correct decisions to unseen vision patterns for the IGVC Autonomous Challenge. A comparison of the Lawrence Technological University robot designs and the design of the other competing schools shows that our platforms were the most affordable robot systems to use as tools for computer science and engineering education. © 2004 Wiley Periodicals, Inc.     

基于机器视觉的航空散热器智能定位钻孔技术

因某型航空散热器再制造的需要，需对产品大量的散热管进行重复的钻孔工作，为解决人工钻孔不便开发的问题开发出一种利用带机器视觉装置的工业机器人对散热器进行定位钻孔的技术。根据产品的特点选用了相应功能的工业机器人与机器视觉装置硬件，给出了智能定位钻孔系统的设计技术方案，建立了系统控制以及软件结构框架。通过最小二乘法对机器视觉采集的图像进行处理，给定了系统坐标标定的过程和方法,明确了机器人定位精度及视觉精度的计量方法。试验结果表明，该系统提高了钻孔效率和精度，可应用于实际生产。     

Research into the application of AI robots in community home leisure interaction

This paper focuses on comprehensive application of artificial intelligence robots for community-based leisure interaction. We propose a multiple-layer perceptron network to design and implement the intelligent interactive home robot system, which includes establishment of an environment map, autonomous navigation, obstacle-avoidance control and human–machine interaction, to complete the positioning and perception functions required by the robot in the home environment. With this system, community residents use an interactive interface to manipulate robots remotely and create an environmental map. In order for the robot to adapt in this changing environment, the robot needs to have a completely autonomous navigation and obstacle-avoidance-control system. In this study, a long-distance obstacle-avoidance fuzzy system and a short-distance anti-fall obstacle-avoidance fuzzy system were used to enable the robot to accommodate unforeseen changes. This technology proved itself capable of navigating a home environment, ensuring that the robot could instantaneously dodge nearby obstacles and correcting the robot’s path of travel. At the same time, it could prevent the robot from falling off a high dropping point and thereby effectively control the robot’s movement trajectory. After combining the above-mentioned multi-sensor and image recognition functions, the intelligent interactive home robot showed that it clearly has the ability to integrate vision, perception and interaction, and we were able to verify that the robot has the necessary adaptability in changing environments and that the design of such interactive robots can be an asset in the home.

     

Design of an autonomous agricultural robot

This paper presents a state-of-the-art review in the development of autonomous agricultural robots including guidance systems, greenhouse autonomous systems and fruit-harvesting robots. A general concept for a field crops robotic machine to selectively harvest easily bruised fruit and vegetables is designed. Future trends that must be pursued in order to make robots a viable option for agricultural operations are focused upon.A prototype machine which includes part of this design has been implemented for melon harvesting. The machine consists of a Cartesian manipulator mounted on a mobile chassis pulled by a tractor. Two vision sensors are used to locate the fruit and guide the robotic arm toward it. A gripper grasps the melon and detaches it from the vine. The real-time control hardware architecture consists of a blackboard system, with autonomous modules for sensing, planning and control connected through a PC bus. Approximately 85% of the fruit are successfully located and harvested.     

Artificial intelligence and robotic assembly

Traditionally, most industrial robots are programmed by teaching. The emergence of robot-level programming languages has improved the programmer's ability to describe and modify the robot moves. However, commercially available robot-level programming languages still fall short of the robot user's need to program complex tasks, and consequently, are not widely used in industry. There is an increasing need for integrating sensors feedback into the robot system to provide better perception and for improving the capacity of the robot to reason and make decisions intelligently in real time.The role of artificial intelligence in programming and controlling robots is discussed. Available robot programming systems including robot-level, object-level, and task-level languages are reviewed. The importance of developing intelligent robots in broadening the scope of flexible automation and opening the door to new robotic applications in space, under water and in harsh environments is outlined. The current development and implementation of programming and control systems for intelligent robots, at McMaster University, are explained. A number of research issues are discussed such as (1) automatic task planning, (2) knowledge representation and use, (3) world modeling, (4) reasoning in automatic assembly planning, and (5) vision monitoring of actions. Examples of geometric, functional, and handling reasoning, as they apply to assembly, are provided. The systems described in this paper are being implemented in the center for flexible manufacturing research and development. Several pieces of hardware are used, including a six-axis articulated robot, a grey-level vision system with a multi-camera, Micro VAX II, and a variety of graphics monitors. The languages available for software development include Common LISP, C, OPS5, VAL II, PASCAL, and FORTRAN 77. The domain of application is currently focused on mechanical assembly.     

视觉图像技术与机器人工件抓取的协作应用

工业机器人在抓取环节如果配置机器视觉装置,应用图像处理技术,在抓取效率和准确度方面就有优势。该文介绍机器人功能实训台的工件抓取视觉系统的组成,侧重工件轮廓的图像处理技术,以图像处理作为机器人视觉系统处理的核心目标,将视觉图像技术与机器人工件抓取技术协作应用于工业机器人实训平台的抓取环节,利用工业机器人运动过程中坐标的转换,通过相机的正确标定与抓取动作的共同控制,实现工件的精确定位,达到可靠抓取的目的。总结图像处理技术在工件抓取中的协作应用效果,期待便捷的视觉图像技术与机器人工件抓取的协作应用。     

嵌入式系统在机器人视觉中的应用

近年来,基于机器视觉的智能机器人在工业等各个领域中得到了广泛的应用。本文针对应用中遇到的一些问题,提出了将机器视觉与嵌入式系统相结合的思想。开发了一种通用的嵌入式系统平台,进行操作系统的移植和图像匹配等算法的研究,并将其应用于移动机器人的视觉导航,取得了较好的效果。     

基于ROS的机器视觉系统实现

Machine vision is used in industrial robot applications for industrial inspection, flaw detection, precision measurement and control, automatic production lines, medicine and various hazardous applications. Based on the open source robot operating sys- tem ROS, this paper uses Kinect binocular vision sensor to obtain 3D stereo vision data, and combines with OpenCV, OpenNI and other open source machine vision libraries to design a low-cost machine vision system using the auxiliary machine vision tools pro- vided by ROS. The experimental test is carried on the prototype.