文献翻译-英汉互译智能机器人

英汉互译一 英文Intelligent RobotsIndustrial robots have been developed to perform a wide variety of manufacturing tasks, such as machine loading/unloading, welding, painting, assembling. However, most industrial robots have very limited sensing ability. For example, if the assembly parts are not presented to the robot in a precise, repetitive fashion, the robot simply can not perform its jobs, because it can not find the part and pick it up. If an invading object happens to enter the work space of a robot, the robot may collide with it, resulting in damage to both, because the robot can not see it as an obstacle. In other words, existing robots are far form being intelligent, and they can not hear, see, and feel (force, shape, texture, temperature, weight, distance and speed of objects in its or nearby).An entirely new phase in robotic applications has been opened with the development of “intelligent robots”. An intelligent robots is basically one that must be capable of sensing its surroundings and possess intelligence enough to respond to a changing environment in must the same way as we do. Such an ability requires the direct application of sensory perception and artificial intelligence. Much of research in robotics has been and is still concerned with how to equip robots with visual sensors-eyes and tactile sensors-the “fingers”. Artificial intelligence will enable the robot to respond to and adapt to changes in its tasks and in its environment, and to reason and make decisions in reaction to those changes.In the light of these requirements, an intelligent robot may be described as one that is equipped with various kinds of sensors, possesses sophisticated signal processing capabilities and intelligence for making decisions, in addition to general mobility.One important capability that humans demonstrate when performing intelligent tasks is receiving sensory information from their surroundings. Human senses provide a rich variety of sensory inputs that are critical to many of the activities performed. Much effort has been made to simulate similar sensory abilities for intelligent robots, among them, vision is the most important sense as it is estimated that up to 80% of sensory information is received by vision. Vision can be bestowed on robotic systems by using imaging sensors in various ways. For improving accuracy of performances, it can help precisely adjust the robot hand by means of optical feedback control using visual sensors. Determining the location, orientation, and recognition of the parts to be picked up is another important application. For example and weld them. Regardless of the application, the vision system must contain an illumination source, an imagery sensor, an imagery digitizer and a system control computer.If ambient lighting serves as illumination source, the imaging process is passive. This type of imaging is common in military applications since the position of the viewer is beyond the control of the viewer. But in industrial applications, controlled illumination or active imaging can be used as freely as possible.The imaging sensor of a robot vision system is defined as an electrooptical device that converts an optical image to a video signal. The image sensor is usually either a TV-camera or a solid-state sensory device, for instance, change-coupled devices(CCD). The latter device offers greater sensitivity, long endurance and light weight, and is thus welcome when compared with the TV-camera.The camera system contains not only the camera detector but also, and very importantly, a lens system. The lens determines the field of view, the depth of focus, and other optical factors the directly affect the quality of the image detected by the camera. Novel techniques, such as a fish-eye lens used to obtain a 360-degree field of view without the need of focus adjustment, have recently been investigated and proved very useful; in mobile robots.Either TV-cameras or CCDs produce an image by generating an analogue value on every pixel, proportional to its light intensity. To enable a digital computer to work with analogue, an analogue-to-digital(A/D) converter is needed to transfer analogue into digital date then stored in the random assess memory(RAM) installed in the computer. The computer analyzes the date and extracts such imagery information as edges, regions, boundaries, colors and textures of the objects in the image. Finally, the computer interprets or understands what the image represents in terms of knowledge about the scene and gives the robot a symbolic description of its environment.Next to vision in importance is tactile sensing or touching. Imagine the blind can do delicate jobs relying on his/her sensitive tactile! A bind robot can be extremely effective in performing an assembly task using only a sense of touch. Touch is of particular importance for providing feedback necessary to grip delicate objects firmly without causing damage to them.To simulate tactile in human hands, a complete tactile-sensing system must perform three fundamental sensing operations:(1) joint force sensing which senses the force applied to the robots hand, wrist and arm joints;(2) touch sensing which senses the pressure applied to various points on the hands surface or the grippers surface;(3) slip sensing which senses any movement of the object while it is being grasped.The joint forces are usually sensed using various strain gauges arranged in the robot wrist assembly. A strain gauge is a force-sensing element whose resistance changes in proportion to the amount of force applied to the element.The simplest application of touch sensor is a gripper that is equipped with an array of miniature microswitches. This type of sensor can only determine the presence or absence of an object at a particular point or an array of point of the robot hand. A more advanced type of touch sensor user arrays of pressure-sensitive piezoelectric material (conductive rubber, conductive foam, etc.). This material conducts electrical current when stressed. This arrangement allows the sensor to perceive changes in force and force and pressure within the robot hand. The size of matrices of tactile sensors ranges from 88 to 8080 2-D arrays. Since the force at each point can be determined, the forces on its surface can be mapped and the shapes of objects grasped in the robot hand can be determined respectively. The force data can be used to display on a TV-like screen the shape of the object and the distribution of force on its surface.Slip sensing is required for a robot to create the optimum of grasping force applied to an delicate, fragile object. This ability prevents damage to the object and allows the object to be picked up without the danger of being dropped. The method used to detect slip is based on sensing any vibration or any movement between the object and the gripper, no matter bow subtle it may be. The gripping force is increased step by step until the object has been firmly grasped and no more slip occurs.The integration of tactile sensing and vision sensing can dramatically enhance adaptive robotic assembly task. An example of this type of sensors would be a vision sensor used to locate and identify objects and position of the robot itself, combined with a tactile sensor used to detect the distribution of force and pressure, determine torque, weight, center of mass and compliance of the material it handles. This hand-eye coordination for general-purpose manipulation would be extremely powerful in the industrial world.Another important sensing for a robot is range, or depth information. The range data are necessary for robot to create its 3-dimensional spatial information when it carries out real-world navigation. Such information is required whether the robot is stationary and navigating its gripper or mobile and navigating its body. For example, consider an industrial bin picking operation where a sensing robot can locate objects of interest in the bin, even though it does not know exactly where they are. The sequence of operations for such a robot might go something like these:(1) Scan the parts in the bin and locate the object of interest in three-dimensional apace.(2) Determine the relative position and orientation of the object.(3) Move its gripper and/or its body to the object location.(4) Position and orient the gripper according to the objects position and orientation.(5) Pick up the object.(6) Place the object at the required location.The first step and the second step in this sequence determine the distance and orientation 二 中文智能机器人工业机器人已经被发展执行各式各样的制造业的任务, 像是载入/卸货，焊接，油漆和装配机器。 然而, 大多数的智能机器人只有有限制的感知能力。例如，如果组合零配件不被精密的重复的样式呈现给机器人,机器人是不能执行它的工作的，因为它不能找到零件而且拾起它。如果一个侵略物件碰巧进入机器人的工作空间,机器人可能和它产生冲突,造成两者的损坏 ,因为机器人不能视它为一个阻挡物。 换句话说，现有的机器人离智能还有很远的距离，而且他们不能听,看和感觉(目标或附近的物件的力，形状，材质，温度，重量，距离和速度)智能机器人发展中的一个全新的机器人的应用程序已经开发使用。 一个智能机器人基本上能够测知它的环境而且持有足够的智能就像我们做的一样去适应环境的改变。 如此能力需要直接的人工智能应用程序。 机器人学的许多研究仍关心如何用视觉的感应器设备和触觉的感应器设备-手指 . 人工智能将会使机器人在它的任务和环境中能够做出回应、适应环境的改变, 推理和做出对那些变化的决断。鉴于这些需求，一个智能机器人可以这样被描述为一个装备各种不同类型的感应器,持有复杂信号处理能力和智能判断力, 除此之外还有灵活性。当它们从外部环境中接受感官信息执行智能任务时，人们论证了一个重要的能力。 人类的感觉提供一个丰富的知觉输入去判断许多进程。 很多的努力是为智能机器人模拟相似的知觉能力, 在它们之中，当它被估计达到80%的感觉信息被视觉收到的时候，视觉是最重要的感觉。 视觉藉由以各种不同的方式使用成像感应器能在机器人系统上被应用。 为改良性能的精确度，它能通过视觉的感应器的光学反馈控制精确的调整机器人手。 决定零配件的位置，定向和辨识整体是另外的重要应用。例如焊接它们。不管应用程序，视觉系统一定要含有一个照度来源，一个成像感应器，一个成像数字转换器和一个系统控制用计算机。如果环境光来源于照度来源, 成像工艺是消极的。成像的这一个型态通常是在军事的应用程序中而超过检视器的控制。但是在工业的应用中，受照度或活跃的图像约束可能尽可能的自由。机器人视觉系统的成像感应器被定义为一个光电转换器件变换光学图像转换成一个视频信号。 图像感应器通常是电视摄影机或一个固态传感装置, 例如,电压耦合元件。后者装置与电视摄影机相比有大的灵敏度，长的持久性和轻的重量，而因此受到欢迎。照相机系统不只是含有照相机传感器, 聚焦系统也非常重要。 镜头的透镜决定视野、焦点深度和其他的光学因数直接影响照相机图像质量。新的技术如鱼眼镜头在不需要镜头调整情况下就可以获得360度的视野, 最近已经被研究出而且被证明在移动的机器人中是非常有用的。摄像机或电压耦合元件都是通过每个像素上的变化的模拟值产生图像,与光强度成正比。 为了使数传计算机能够处理模拟量 ,模数转换器(A/D)得将模拟信号转换成数字信号，然后保存在计算机的随机存储器（RAM）。计算机分析数据和摘要，例如图像对象的边缘，区域，交界，颜色和材质信息。最后，计算机解释或理解图像代表什么是根据关于景物的信息和机器人对它的环境的象征性描述。仅次于视觉的是触觉感知或触摸。 想像一下盲人能做细致的工作完全仰赖他/她的敏感触觉! 一个盲的机器人能够极其有效的履行工作仅仅是依赖于触觉。触觉在没有对它们损坏的情况下对提供特殊重要的反馈必须精巧而稳定的把握。模拟触觉掌握在人类的手中，一个完全触觉感知系统必须执行三个基本感知运算：（1）感觉联合的连接被应用到机器人的手，手腕和手臂上;(2)触觉被应用的压力对于在手的表面或抓取装置的表面方面有各种不同的点;(3)感觉对于当它正在被抓住的任何运动的物件有转差率测知。结点力通常由各种不同的被安装到机器人关节装置中的应变计测知。应变计是电阻的变化与应用到元件上的力成比例变化的元件。触觉感应器的最简单应用是装备成一个小规模微型开关的排列。这一类型的感应器只能决定对象在特殊点或机器手的行列中的某一点的存在或不存在。一个更高级的触觉感应器使用压敏压电材料的阵列(导电橡皮，导电泡沫,等等)。当受到压力时这种材料将引导电流。 这种排列允许感应器在机器人手里面感觉在力方面的改变。 触觉感应器的矩阵排列尺寸从88到8080 2-D。每个点上的力能被决定，它们表面的力能被映射，而且在机器人手中被抓住的物件形状可以被分别的决定。 力的数据可以用像电视屏一样显示物体的形状和力的表面分布。滑动的测知需要机器人建立一个最佳的力量以应用于精巧的和易碎的物体。 这种能力可以避免对物件造成伤害而且允许物体在没有危险或坠落的情况下被捡起。 这种方法通常是基于感觉任何物体和机械爪之间的振动或运动来探测滑动的，不论凹度是否精细。这种引起人注意的能力一步一步增加直到物件被坚固抓住，而且没有较多的转差发生。触觉测知和视觉测知的集成能引人注意地提高机器人适应装配任务。例如这种类型的感应器有可能是视觉感应器被用于机器人自己定位对象和位置,与触觉的感应器结合可以探测到压力的分布,决定它处理事物的回转力矩，重量，质量中心和材料的手感柔软度。手-眼的多方面协调在工业的世界中的操作是极其有力的。机器人的另外重要感觉就是测知范围或深度的信息。 范围数据是当机器人实施真实世界的导航时必需让机器人产生它的3维空间的空间信息。如此的信息需要机器人是否是平稳的导航它的夹子或移动的导航它自己。举例来说,考虑一个工业的箱拾取操作时,机器人可以感觉定位箱子的目标，即使它不完全地知道它们在哪里。机器如此人的运算操作顺序可能像这些:(1)扫瞄箱的零配件而且在三维空间里定位物件(2)决定物件的相对位置和方向(3)移动它的夹子或它的身体到物件位置(4)依照物件的位置和方向放置和定向夹子(5)拾起物件(6)放置物件到需要的位置第一个阶段和第二个阶段在这些顺序里决定在3维或3D空间内与目标相关的距离和定向。