【機械類畢業(yè)論文中英文對照文獻(xiàn)翻譯】機器人,機械類畢業(yè)論文中英文對照文獻(xiàn)翻譯,機械類,畢業(yè)論文,中英文,對照,對比,比照,文獻(xiàn),翻譯,機器人 攀枝花學(xué)院 Panzhihua University 本科畢業(yè)設(shè)計（論文） 英文翻譯 工業(yè)機械手模型控制系統(tǒng)設(shè)計 院 （系）： 機電工程學(xué)院 專 業(yè)： 機械設(shè)計制造及其自動化 班 級： 03級機制一班 學(xué)生姓名： 劉 洋 學(xué) 號:200310621044 二00七年 4月29日 6 -攀枝花學(xué)院本科畢業(yè)設(shè)計 英文翻譯 Robotics The Robotics Application Many of the robots in use tody do jobs that are especially difficult for human worker. These are the types of jobs that require great strength or pose danger. For example, robots are particularly useful in the auto-manufacturing industry where parts of automobiles must be welded together. A welding tool used by a human worker weighs about 100 pounds or more and is difficult to handle. As mechanical supermen, robots may be called upon to do anything from moving heay components between workstations on a factory floor to carrying bags of cement. Spray painting is another task suited to robots because robots do not need to breathe. Unlike human painters, they are unaffected by the poisonous fumes. Robots are better at this task, not because they are faster or cheaper than humans, but because they work in a place where humans cannot. Third in the list of useful jobs for robots is the assembly of electronnic parts. Robots shine at installing chips in printed circuit boards because of a capability that robots have that people don’t . A robot, one properly programmed, will not put a chip in the wrong place. This automatic accuracy is particularly valuable in this kind of industry because locating and fixing mistakes is costly. Robotics Revolution Earlier robots were usually blind and deaf, but newer types of robots are fitted with video cameras and other sensing devices that can detect heat, texture, size, and sound. These robots are used in space projects, nuclear stations, and underwater exporation research. Inther efforts to expand the range of robotic applications, reseachers are looking beyon traditional designs to examine a variety of potential models from the biological world. The industrial arm is a classic example. Scientists have been able to model robots to imitate the vertebrate spine of a snake in order to paint the interior of automobiles. They have simulated the muscle structure and movement of an elephant’s trunk in an attempt to create a robotic arm capable of lifting heavy objects. Scientists also emulate the flexibility of an octopus where the tentacles can conform to the fragile objects of any shape and hold them with uniform, gentle pressure. A variation of this design can be used to handle animals, turn hospital patients in their beds, or lift asmall child. The challenge of equipping robots with the skills to operate independently, outside of a factory or laboratory, has taxed theingenuity and creativity of academic, military, and industral scientists for years. Simply put, robot hands-like robot legs, or eyes, orreasoning powers-have long way to go before they can approach what biological evlution has achieved over by the course of hundreds of millions of years. Much more will have to happen in laboratories around the world before the robots can be compared to nature’s handiwork. In the meantime, the robotics revolution is already beginning to change the kind of work that people do. The boring and dangerous jobs are now assumed by robots. By the turn of the century, more and more humans will be required for tasks that machine can not do. There are slso some industrialists who hope that by the year 2000 all their empoyee will be knowledge workers, no longer standing on assembly lines but rather sitting at desks and computer terminals to deal with information. These changes are already under way, and their pace accelerates every year. Intelligent Robots A new phase in robot applications has been opened with the development of “intelligent robots”. An intelligent robot is bascally one that must be capable of sensing its surrounding and possess intelligence enough to respond to a changing environment in much the same way as we do. Such ability requires the direct application of sensory perception and artificial intelligence. Much of reseach 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 changes in its task and in its environment, and to reason and make decisions in reactiong to those changes. Visional Sensory Much effort has been made to simulate similar human sensory abilities for inelligent 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 performance, 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. Among the vision system, one of the key components is imagery sensor. The imagery sensor of a robot system is defined as an electro-optical 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 exanple, change-couple devices(CCD). The latter device offers greater sensitivity, long endurance and lightweight, and is thus welcome when compared with the TV-camera. The camera system contains not only the camera detector but also, and very importantly, alens system. The lens determines the field of view, the depth of focous, ans other optical factors that directly affect the quality of the image detected by the camera. Either TV-camera 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 this signal, an analongue-to-digital(A/D) converter is needed to transfer analogue into digital data, then stored in random access menory(RAM), installed in computer. The computer analyzes the data and extracts such imagery information as edges, 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. Tactile Sensory Next to vision in importance is tactile sensing or touching. Imagine the blind can do delicate jobs relying on his/her sensitive tactile. A blind 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 peform three fundmental sensing perations: (1)joint force sensing which senses the force applies to robot’s hand, wrist and arm joints; (2)touch sensing which sense the preeure applied to various points on the hand’s surface or the gripper’s surface; (3)slip sensing which senses any movement of the object while it is being graspeed. The joint forces are usually sensed using various strain gauges arranged in robotwrist assembly. A strain gauge is a force-sensing element whose resistance changes in proportion to the amount of the force applied to the element. The simplest application of touch sensor is gripper 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 points of the robot hand. A more advanced type of touch sensors uses arrays of pressure-sensitive piezoelectric material (conductive rubber or foam, etc.). The arrangement allows the sensor to perceive changes in force and pressure within the robothand. Since the force at each point can be determined, the force on its surface can be mapped and the shapes of objects grasped in the robot hand be determined respectively. Slip sensing is required for a robot to create the optimum amount of grasping force applied to a delicate, fragile object. This ability prevents damage to the object and allows the object to be picked up without the danger of being droped. 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 robotic assembly task. An example of this type of sensors would be a vision used to locate and identify objects and position of the robot itself, combined with a tactile sensor usedto detech the distribution of force and pressure, and determine torque, weight, center of mass and compliance of the material it handle. The hand-eye coordination for general- purpose manipulation will be extremely powerful in the industrial world. 機器人 機器人應(yīng)用 許多今天使用的機器人在做一些對工人特別困難的工作.這些類型的工作需要很大的力量,或者有危險.比如,在需要將汽車零件焊接在一起的自動生產(chǎn)工業(yè)中,機器人就特別有用,工人使用的焊接工具重約100磅,或更重,并且很難操作。作為機械巨人,機器人可以被呼喚去做任何事情,從一工場的工作站點之間移動笨重部件到到運送袋裝的水泥。 由于機器人不需要呼吸，所以噴涂是另一個適合機器人的任務(wù)，不像油漆工，機器人不受有毒氣體的影響。機器人更優(yōu)于完成這種工作，不但因為它們比人做得更快更便宜，而且因為能在人不能工作的地方進行工作。 適合于機器人工作中，第三個項目是裝配電子元件。機器人能很好地將芯片裝配在印刷電路板上，因為它具備人所沒有具備的能力。一旦適當(dāng)?shù)鼐幊?，機器人就不會將芯片放錯地方。這種自動的精度在這種類型的工業(yè)中特別有價值，因為定位和安裝錯誤代價是很高的。 機器人革命 早期的機器人又瞎又聾，但新型機器人安裝有電視攝像機和其他傳感設(shè)備，因而能感知熱、結(jié)構(gòu)、尺寸和聲音，這些機器人用于空間計劃、核反應(yīng)堆和水下探測研究。 在擴大機器人應(yīng)用范圍的嘗試中，研究者正超越傳統(tǒng)設(shè)計，并考慮源自生物世界的各種潛在模型，工業(yè)機械手是一個典型的例子。科學(xué)家已能讓機器人模仿蛇的脊椎，以油漆汽車內(nèi)部。在著力建造能舉起重物體的機器人的手臂時，他們模仿肌肉結(jié)構(gòu)和大象鼻子的運動?？茖W(xué)家還模擬章魚的靈活性，其觸角能用于任何形狀的易碎品，并用均勻且輕柔的壓力握住這些易碎品。這種設(shè)計的一種變化能用于抱起動物，給醫(yī)院中病床上的病人翻身，或抱起小孩。 機器人有在工廠或?qū)嶒炇彝猹毩⒉僮鞯募寄?，這一挑戰(zhàn)已花費了學(xué)術(shù)界、軍世界和工業(yè)界的科學(xué)家們的智謀和創(chuàng)造性。簡單來說，機器人的手——如同機器人的腿、眼睛或推理能力。在接近經(jīng)過成億年生物進化所獲得的能力之前，還有很長的路要走。在機器人能和自然的杰作相比之前，在世界各地的實驗室中還需完成許多工作。 同時，機器人的進展已開始轉(zhuǎn)變?nèi)怂龅墓ぷ?，令人厭煩和危險的工作已由機器人承擔(dān)。在世紀(jì)之交，更多更多的人要去完成機器所不能完成的任務(wù)。已有許多工業(yè)家希望到2000以后，所有的雇員都是知識工，不再站在裝配線前，而是坐在桌子和計算機終端前處理信息。這些變化已經(jīng)存在，而且其步伐每年都在加快。 智能機器人 一個機器人應(yīng)用中的新局面隨著“智能機器人”的發(fā)展而已經(jīng)打開。一個智能機器人基本上能感知環(huán)境并且具有足夠的智力，像我們?nèi)艘粯幽軐ψ兓沫h(huán)境作出響應(yīng)。這種能力要求直接使用感覺和人工智能。許多機器人的研究已經(jīng)，并且仍然關(guān)注如何在機器人中裝備視覺傳感器——眼睛和觸覺傳感——“手指”。人工智能將使機器人能響應(yīng)并適應(yīng)其工作任務(wù)和環(huán)境變化，并且能按照這些變化的反應(yīng)進行推理和作出決定。 視覺傳感 為使機器人模仿人的感覺能力，已作了很多的努力。其中，視覺是最重要的感覺，因為據(jù)估計，接近80％的感覺信息是由視覺收到的。機器人系統(tǒng)中設(shè)置視覺可由各種形式的圖象傳感器來完成。為了改善運行的精度，通過視覺傳感器的光學(xué)反饋控制，可精密地調(diào)整機器人手臂。決定位置、方向和辨別所要選取得零件則是另一重要的應(yīng)用。 在視覺系統(tǒng)中，關(guān)鍵部件之一是圖象傳感器。機器人系統(tǒng)中的圖象傳感器的定義為將光學(xué)圖象轉(zhuǎn)換成視頻信號的電－光學(xué)器件。圖象傳感器通常為電視攝像機，或固態(tài)傳感器件，如電荷耦合器件（CCD）。后一種器件提供更高的靈敏度、較長的耐久性和較輕的重量，因而與電視攝像機相比更受歡迎。攝像系統(tǒng)不但包括攝像探測器，而且更重要的是包括光學(xué)透鏡系統(tǒng)。這種透鏡決定視場、定焦深度和其他直接影響攝像機所攝圖象質(zhì)量的光學(xué)特性。 無論電視攝像機還是CCD都會通過在每一象素點形成與光強成正比的模擬量而產(chǎn)生圖象。要使數(shù)字計算機對信號起作用，需要模擬數(shù)字（A/D）轉(zhuǎn)換器將模擬數(shù)據(jù)轉(zhuǎn)換成數(shù)字?jǐn)?shù)據(jù)，然后存儲在計算機內(nèi)的隨機存取存儲器（RAM）中。計算機分析這些數(shù)據(jù)并抽取某些信息，如邊界、區(qū)域、顏色，以及圖象中物體結(jié)構(gòu)。最后，計算機能就場景的辨別、理解圖象所表示的含義或作出解釋，并使機器人用符號對環(huán)境的描述。 接觸感覺 重要性僅次于視覺是接觸感覺，或觸感。想象一下盲人能依靠靈敏的觸覺來做精細(xì)的工作。無視覺機器人能只用觸覺極有效地完成裝配任務(wù)，對于需要反饋來緊緊握住精致脆弱的物體而不會損壞它們的用途，觸覺具有獨特的重要性。 為了模擬人手的觸覺，一完整的接觸傳感系統(tǒng)必須完成三個基本操作：（1）關(guān)節(jié)的力覺，檢測加在機器人的手、腕和臂關(guān)節(jié)上的力；（2）觸覺檢測，加在手平面或者夾持器平面各個點上的壓力；（3）滑覺，檢測所抓取的物體的任何滑動。 關(guān)節(jié)上的力通常用各種布置在機器人手腕零件上的應(yīng)變測力計來檢測。應(yīng)變測力計是一種測力元件，其電阻變化與加在元件上的力大小成比例。最簡易的觸覺傳感器是用細(xì)小的微型開關(guān)陣列組成的夾持器。這種傳感器只能決定物體是否在機器人手上的點陣中某個特殊點上存在。更為先進的觸覺傳感器使用壓敏的壓電材料（如導(dǎo)電橡膠或泡沫等）。其排列使傳感器能感覺機器人手中的力和壓力的變化。既然各點上的力可以決定，所以手掌面上的力就可被圖象化地獲得，并由此決定機器人手中所握物體的形狀。對于產(chǎn)生一個用于精致脆弱物體的最佳握持力，機器人需要滑覺。這種能力避免損壞物體，并能抓起物體而不會有掉下的危險。夾持力一步一步增加，直至物體被緊緊抓住而不再有滑動。 觸覺和視覺的集成能極大地提高機器人的裝配工作，這類傳感器的一例是是覺傳感器，用于對物體和機器人本身的定位和辨別；并結(jié)合觸覺傳感器用于探測力和壓力的分布和確定力矩、重量、重心，安所抓取的材料決定握持力。這種用于通用的手眼配合操作在工業(yè)界將會變得極為有效力。