机器人技术发展中英文对照外文翻译文献

中英文对照资料外文翻译文献FEM Optimization for Robot StructureAbstractIn optimal design for robot structures, design models need to he modified and computed repeatedly. Because modifying usually can not automatically be run, it consumes a lot of time. This paper gives a method that uses APDL language of ANSYS 5.5 software to generate an optimal control program, which mike optimal procedure run automatically and optimal efficiency be improved.1）IntroductionIndustrial robot is a kind of machine, which is controlled by computers. Because efficiency and maneuverability are higher than traditional machines, industrial robot is used extensively in industry. For the sake of efficiency and maneuverability, reducing mass and increasing stiffness is more important than traditional machines, in structure design of industrial robot.A lot of methods are used in optimization design of structure. Finite element method is a much effective method. In general, modeling and modifying are manual, which is feasible when model is simple. When model is complicated, optimization time is longer. In the longer optimization time, calculation time is usually very little, a majority of time is used for modeling and modifying. It is key of improving efficiency of structure optimization how to reduce modeling and modifying time.APDL language is an interactive development tool, which is based on ANSYS and is offered to program users. APDL language has typical function of some large computer languages. For example, parameter definition similar to constant and variable definition, branch and loop control, and macro call similar to function and subroutine call, etc. Besides these, it possesses powerful capability of mathematical calculation. The capability of mathematical calculation includes arithmetic calculation, comparison, rounding, and trigonometric function, exponential function and hyperbola function of standard FORTRAN language, etc. By means of APDL language, the data can be read and then calculated, which is in database of ANSYS program, and running process of ANSYS program can be controlled.Fig. 1 shows the main framework of a parallel robot with three bars. When the length of three bars are changed, conjunct end of three bars can follow a given track, where robot hand is installed. Core of top beam is triangle, owing to three bars used in the design, which is showed in Fig.2. Use of three bars makes top beam nonsymmetrical along the plane that is defined by two columns. According to a qualitative analysis from Fig.1, Stiffness values along z-axis are different at three joint locations on the top beam and stiffness at the location between bar 1 and top beam is lowest, which is confirmed by computing results of finite element, too. According to design goal, stiffness difference at three joint locations must he within a given tolerance. In consistent of stiffness will have influence on the motion accuracy of the manipulator under high load, so it is necessary to find the accurate location of top beam along x-axis.To the questions presented above, the general solution is to change the location of the top beam many times, compare the results and eventually find a proper position, The model will be modified according to the last calculating result each time. It is difficult to avoid mistakes if the iterative process is controlled manually and the iterative time is too long. The outer wall and inner rib shapes of the top beam will be changed after the model is modified. To find the appropriate location of top beam, the model needs to be modified repetitiously.Fig. 1 Solution of Original DesignThis paper gives an optimization solution to the position optimization question of the top beam by APDL language of ANSYS program. After the analysis model first founded, the optimization control program can be formed by means of modeling instruction in the log file. The later iterative optimization process can be finished by the optimization control program and do not need manual control. The time spent in modifying the model can be decreased to the ignorable extent. The efficiency of the optimization process is greatly improved.2）Construction of model for analysisThe structure shown in Fig. 1 consists of three parts: two columns, one beam and three driving bars. The columns and beam are joined by the bolts on the first horizontal rib located on top of the columns as shown in Fig.1. Because the driving bars are substituted by equivalentforces on the joint positions, their structure is ignored in the model.The core of the top beam is three joints and a hole with special purpose, which can not be changed. The other parts of the beam may be changed if needed. For the convenience of modeling, the core of the beam is formed into one component. In the process of optimization, only the core position of beam along x axis is changed, that is to say, shape of beam core is not changed. It should be noticed that, in the rest of beam, only shape is changed but the topology is not changed and which can automatically be performed by the control program.Fig.1, six bolts join the beam and two columns. The joint surface can not bear the pull stress in the non-bolt joint positions, in which it is better to set contact elements. When the model includes contact elements, nonlinear iterative calculation will be needed in the process of solution and the computing time will quickly increase. The trial computing result not including contact element shows that the outside of beam bears pulling stress and the inner of beam bears the press stress. Considering the primary analysis object is the joint position stiffness between the top beam and the three driving bars, contact elements may not used, hut constructs the geometry model of joint surface as Fig.2 showing. The upper surface and the undersurface share one key point in bolt-joint positions and the upper surface and the under surface separately possess own key points in no bolt positions. When meshed, one node will be created at shared key point, where columns and beam are joined, and two nodes will be created at non shared key point, where column and beam are separated. On right surface of left column and left surface of right column, according to trial computing result, the structure bears press stress. Therefore, the columns and beam will share all key points, not but at bolts. This can not only omit contact element but also show the characteristic of bolt joining. The joining between the bottoms of the columns and the base are treated as full constraint. Because the main aim of analysis is the stiffness of the top beam, it can be assumed that the joint positions hear the same as load between beam and the three driving bars. The structure is the thin wall cast and simulated by shell element . The thickness of the outside wall of the structure and the rib are not equal, so two groups of real constant should he set. For the convenience of modeling, the two columns are alsoset into another component. The components can create an assembly. In this way, the joint positions between the beam core and columns could he easily selected, in the modifying the model and modifying process can automatically be performed. Analysis model is showed Fig.1. Because model and load are symmetric, computing model is only half. So the total of elements is decreased to 8927 and the total of nodes is decreased to 4341. All elements are triangle.3.）Optimization solutionThe optimization process is essentially a computing and modifying process. The original design is used as initial condition of the iterative process. The ending condition of the process is that stiffness differences of the joint locations between three driving bars and top beam are less than given tolerance or iterative times exceed expected value. Considering the speciality of the question, it is foreseen that the location is existent where stiffness values are equal. If iterative is not convergent, the cause cannot be otherwise than inappropriate displacement increment or deficient iterative times. In order to make the iterative process convergent quickly and efficiently, this paper uses the bisection searching method changing step length to modify the top beam displacement. This method is a little complex but the requirement on the initial condition is relatively mild.The flow chart of optimization as follows:1. Read the beam model data in initial position from backup file;2. Modify the position of beam;3. Solve;4. Read the deform of nodes where beam and three bars are joined;5. Check whether the convergent conditions are satisfied, if not, then continue to modify the beam displacement and return to 3, otherwise, exit the iteration procedure.6. Save the results and then exit.The program's primary control codes and their function commentaries are given in it, of which the detailed modeling instructions are omitted. For the convenience of comparing with the control flow, the necessary notes are added.the flag of the batch file in ANSYSBATCH RESUME, robbak.db, 0read original data from the backupfile robbak,.db/PREP7 enter preprocessordelete the joint part between beam core and columnsmove the core of the beam by one :step lengthapply load and constraint on the geometry meshing thejoint position between beam core and columns FINISH exit the preprocessorISOLU enter solverSOLVE solveFINISH exit the solverPOST1 enter the postprocessor*GET ,front,NODE,2013,U,Z read the deformation of first joint node on beam*GET,back,NODE, 1441 ,U,Z read the deformation of second joint node on beam intoparameter hacklastdif-1 the absolute of initial difference between front and hacklast timeflag=- 1 the feasibility flag of the optimizationstep=0.05 the initial displacement from initial position to the currentposition*D0,1,1,10,1 the iteration procedure begin, the cycle variable is I andits value range is 1-10 and step length is 1dif=abs(front-back) the absolute of the difference between front and hack inthe current result*IF,dif,LE,l .OE-6,THEN check whether the absolute difference dif satisfies therequest or noflag=l yes, set flag equal to 1*EXIT exit the iterative calculation*ELSEIF,dif,GE,lastdif,THEN check whether the dif value becomes great or not flag=2yes, set flag 2 modify step length by bisection methodperform the next iterative calculation, use the lastposition as the current position and modified last steplength as the current step lengthELSE if the absolute of difference value is not less thanexpected value and become small gradually, continue tomove top beam read the initial condition from back upfile enter the preprocessorMEN, ,P51X, , , step,, , ,1 move the core of the beam by one step length modify thejoint positions between beam core and column applyload and constraint meshingFINISH exit preprocessorISOLU enter solverSOLVE solveFINISH exit the solver/POST1 exit the postprocessor*GET,front,NODE,201 3,U,Z read the deformation of first joint node to parameter front *GET,back,NODE, 144 1,U,Z read the deformation of second joint node to parameter back lastdif-dif update the value of last dif*ENDIF the end of the if-else*ENDDO the end of the DO cycleMost of the control program above is copied from log file, which is long. The total of lines is up to about 1000 lines. Many codes such as modeling and post-process codes are used repeatedly. To make the program construct clear, these instructions can he made into macros, which are called by main program. This can efficiently reduce the length of the main program. In addition, modeling instructions from log file includes lots of special instructions that are only used under graphic mode but useless under hatch mode. Deleting and modifying these instructions when under batch mode in ANSYS can reduce the length of the file, too.In the program above, the deformation at given position is read from node deformation. In meshing, in order to avoid generating had elements, triangle mesh is used. In optimization, the shape of joint position between columns and beam continually is changed. This makes total of elements different after meshing each time and then element numbering different, too. Data read from database according to node numbering might not he data to want. Therefore, beam core first needs to he meshed, then saved. When read next time, its numbering is the same as last time.Evaluating whether the final result is a feasible result or not needs to check the flag value. If only the flag value is I, the result is feasible, otherwise the most proper position is not found. The total displacement of top beam is saved in parameter step. If the result is feasible, the step value is the distance from initial position to the most proper position. The sum of iterative is saved in parameter 1. According to the final value of I, feasibility of analysis result and correctness of initial condition can he evaluated.4）Optimization resultsThe sum of iterative in optimization is seven, and it takes about 2 hour and 37 minutes to find optimal position. Fig.3 shows the deformation contour of the half-construct. In Fig.3, the deformations in three joints between beam and the three driving bars is the same as level, and the corresponding deformation range is between -0.133E-04 and -0.1 15E-O4m, the requirement of the same stiffness is reached. At this time, the position of beam core along x-axis as shown in Fig. 1 has moved -0.71E-01m compared with the original designed positionBecause the speed of computer reading instruction is much faster than modifying model manually, the time modifying model can be ignored. The time necessary foroptimization mostly depends on the time of solution. Compared with the optimization procedure manually modifying model, the efficiency is improved and mistake operating in modeling is avoided.5）ConclusionThe analyzing result reveals that the optimization method given in this paper is effective and reaches the expected goal. The first advantage of this method is that manual mistakes do not easily occur in optimization procedure. Secondly, it is pretty universal and the control codes given in this paper may he transplanted to use in similar structure optimization design without large modification. The disadvantage is that the topology structure of the optimization object can not be changed. The more the workload of modifying the model, the more the advantages of this method are shown. In addition, the topology optimization function provided in ANSYS is usedto solve the optimization problem that needs to change the topology structure.The better optimization results can he achieved if the method in this paper combined with it.中文译文：机器人机构优化设计有限元分析摘要机器人结构最优化设计，设计模型需要反复的修正和计算。

外文出处：《Manufacturing Engineering and Technology—Machining》附件1：外文原文ManipulatorRobot developed in recent decades as high-tech automated production equipment. I ndustrial robot is an important branch of industrial robots. It features can be program med to perform tasks in a variety of expectations, in both structure and performance a dvantages of their own people and machines, in particular, reflects the people's intellig ence and adaptability. The accuracy of robot operations and a variety of environments the ability to complete the work in the field of national economy and there are broad p rospects for development. With the development of industrial automation, there has be en CNC machining center, it is in reducing labor intensity, while greatly improved lab or productivity. However, the upper and lower common in CNC machining processes material, usually still use manual or traditional relay-controlled semi-automatic device . The former time-consuming and labor intensive, inefficient; the latter due to design c omplexity, require more relays, wiring complexity, vulnerability to body vibration inte rference, while the existence of poor reliability, fault more maintenance problems and other issues. Programmable Logic Controller PLC-controlled robot control system for materials up and down movement is simple, circuit design is reasonable, with a stron g anti-jamming capability, ensuring the system's reliability, reduced maintenance rate, and improve work efficiency. Robot technology related to mechanics, mechanics, elec trical hydraulic technology, automatic control technology, sensor technology and com puter technology and other fields of science, is a cross-disciplinary integrated technol ogy.First, an overview of industrial manipulatorRobot is a kind of positioning control can be automated and can be re-programmed to change in multi-functional machine, which has multiple degrees of freedom can be used to carry an object in order to complete the work in different environments. Low wages in China, plastic products industry, although still a labor-intensive, mechanical hand use has become increasingly popular. Electronics and automotive industries thatEurope and the United States multinational companies very early in their factories in China, the introduction of automated production. But now the changes are those found in industrial-intensive South China, East China's coastal areas, local plastic processin g plants have also emerged in mechanical watches began to become increasingly inter ested in, because they have to face a high turnover rate of workers, as well as for the workers to pay work-related injuries fee challenges.With the rapid development of China's industrial production, especially the reform and opening up after the rapid increase in the degree of automation to achieve the wor kpiece handling, steering, transmission or operation of brazing, spray gun, wrenches a nd other tools for processing and assembly operations since, which has more and mor e attracted our attention. Robot is to imitate the manual part of the action, according to a given program, track and requirements for automatic capture, handling or operation of the automatic mechanical devices.In real life, you will find this a problem. In the machine shop, the processing of part s loading time is not annoying, and labor productivity is not high, the cost of producti on major, and sometimes man-made incidents will occur, resulting in processing were injured. Think about what could replace it with the processing time of a tour as long a s there are a few people, and can operate 24 hours saturated human right? The answer is yes, but the robot can come to replace it.Production of mechanical hand can increase the automation level of production and labor productivity; can reduce labor intensity, ensuring product quality, to achieve saf e production; particularly in the high-temperature, high pressure, low temperature, lo w pressure, dust, explosive, toxic and radioactive gases such as poor environment can replace the normal working people. Here I would like to think of designing a robot to be used in actual production.Why would a robot designed to provide a pneumatic power: pneumatic robot refers to the compressed air as power source-driven robot. With pressure-driven and other en ergy-driven comparison have the following advantages: 1. Air inexhaustible, used late r discharged into the atmosphere, does not require recycling and disposal, do not pollu te the environment. (Concept of environmental protection) 2. Air stick is small, the pipeline pressure loss is small (typically less than asphalt gas path pressure drop of one-thousandth), to facilitate long-distance transport. 3. Compressed air of the working pre ssure is low (usually 4 to 8 kg / per square centimeter), and therefore moving the mate rial components and manufacturing accuracy requirements can be lowered. 4. With th e hydraulic transmission, compared to its faster action and reaction, which is one of th e advantages pneumatic outstanding. 5. The air cleaner media, it will not degenerate, n ot easy to plug the pipeline. But there are also places where it fly in the ointment: 1. A s the compressibility of air, resulting in poor aerodynamic stability of the work, resulti ng in the implementing agencies as the precision of the velocity and not easily control led. 2. As the use of low atmospheric pressure, the output power can not be too large; i n order to increase the output power is bound to the structure of the entire pneumatic s ystem size increased.With pneumatic drive and compare with other energy sources drive has the followin g advantages:Air inexhaustible, used later discharged into the atmosphere, without recycling and disposal, do not pollute the environment. Accidental or a small amount of leakage wo uld not be a serious impact on production. Viscosity of air is small, the pipeline pressu re loss also is very small, easy long-distance transport.The lower working pressure of compressed air, pneumatic components and therefor e the material and manufacturing accuracy requirements can be lowered. In general, re ciprocating thrust in 1 to 2 tons pneumatic economy is better.Compared with the hydraulic transmission, and its faster action and reaction, which is one of the outstanding merits of pneumatic.Clean air medium, it will not degenerate, not easy to plug the pipeline. It can be saf ely used in flammable, explosive and the dust big occasions. Also easy to realize auto matic overload protection.Second, the composition, mechanical handRobot in the form of a variety of forms, some relatively simple, some more complic ated, but the basic form is the same as the composition of the , Usually by the implem enting agencies, transmission systems, control systems and auxiliary devices composed.1.Implementing agenciesManipulator executing agency by the hands, wrists, arms, pillars. Hands are crawlin g institutions, is used to clamp and release the workpiece, and similar to human finger s, to complete the staffing of similar actions. Wrist and fingers and the arm connecting the components can be up and down, left, and rotary movement. A simple mechanical hand can not wrist. Pillars used to support the arm can also be made mobile as needed .2. TransmissionThe actuator to be achieved by the transmission system. Sub-transmission system c ommonly used manipulator mechanical transmission, hydraulic transmission, pneuma tic and electric power transmission and other drive several forms.3. Control SystemManipulator control system's main role is to control the robot according to certain p rocedures, direction, position, speed of action, a simple mechanical hand is generally not set up a dedicated control system, using only trip switches, relays, control valves a nd circuits can be achieved dynamic drive system control, so that implementing agenc ies according to the requirements of action. Action will have to use complex program mable robot controller, the micro-computer control.Three, mechanical hand classification and characteristicsRobots are generally divided into three categories: the first is the general machinery does not require manual hand. It is an independent not affiliated with a particular host device. It can be programmed according to the needs of the task to complete the oper ation of the provisions. It is characterized with ordinary mechanical performance, also has general machinery, memory, intelligence ternary machinery. The second category is the need to manually do it, called the operation of aircraft. It originated in the atom, military industry, first through the operation of machines to complete a particular job, and later developed to operate using radio signals to carry out detecting machines suc h as the Moon. Used in industrial manipulator also fall into this category. The third cat egory is dedicated manipulator, the main subsidiary of the automatic machines or automatic lines, to solve the machine up and down the workpiece material and delivery. T his mechanical hand in foreign countries known as the "Mechanical Hand", which is t he host of services, from the host-driven; exception of a few outside the working proc edures are generally fixed, and therefore special.Main features:First, mechanical hand (the upper and lower material robot, assembly robot, handlin g robot, stacking robot, help robot, vacuum handling machines, vacuum suction crane, labor-saving spreader, pneumatic balancer, etc.).Second, cantilever cranes (cantilever crane, electric chain hoist crane, air balance th e hanging, etc.)Third, rail-type transport system (hanging rail, light rail, single girder cranes, doubl e-beam crane)Four, industrial machinery, application of handManipulator in the mechanization and automation of the production process develo ped a new type of device. In recent years, as electronic technology, especially comput er extensive use of robot development and production of high-tech fields has become a rapidly developed a new technology, which further promoted the development of ro bot, allowing robot to better achieved with the combination of mechanization and auto mation.Although the robot is not as flexible as staff, but it has to the continuous duplication of work and labor, I do not know fatigue, not afraid of danger, the power snatch weig ht characteristics when compared with manual large, therefore, mechanical hand has b een of great importance to many sectors, and increasingly has been applied widely, for example:(1) Machining the workpiece loading and unloading, especially in the automatic lat he, combination machine tool use is more common.(2) In the assembly operations are widely used in the electronics industry, it can be used to assemble printed circuit boards, in the machinery industry It can be used to ass emble parts and components.(3) The working conditions may be poor, monotonous, repetitive easy to sub-fatigue working environment to replace human labor.(4) May be in dangerous situations, such as military goods handling, dangerous go ods and hazardous materials removal and so on..(5) Universe and ocean development.(6), military engineering and biomedical research and testing.Help mechanical hands: also known as the balancer, balance suspended, labor-saving spreader, manual Transfer machine is a kind of weightlessness of manual load system, a novel, time-saving technology for material handling operations booster equipment, belonging to kinds of non-standard design of series products. Customer application ne eds, creating customized cases. Manual operation of a simulation of the automatic ma chinery, it can be a fixed program draws ﹑ handling objects or perform household to ols to accomplish certain specific actions. Application of robot can replace the people engaged in monotonous ﹑ repetitive or heavy manual labor, the mechanization and a utomation of production, instead of people in hazardous environments manual operati on, improving working conditions and ensure personal safety. The late 20th century, 4 0, the United States atomic energy experiments, the first use of radioactive material ha ndling robot, human robot in a safe room to manipulate various operations and experi mentation. 50 years later, manipulator and gradually extended to industrial production sector, for the temperatures, polluted areas, and loading and unloading to take place t he work piece material, but also as an auxiliary device in automatic machine tools, ma chine tools, automatic production lines and processing center applications, the comple tion of the upper and lower material, or From the library take place knife knife and so on according to fixed procedures for the replacement operation. Robot body mainly b y the hand and sports institutions. Agencies with the use of hands and operation of obj ects of different occasions, often there are clamping ﹑ support and adsorption type of care. Movement organs are generally hydraulic pneumatic ﹑﹑ electrical device dri vers. Manipulator can be achieved independently retractable ﹑ rotation and lifting m ovements, generally 2 to 3 degrees of freedom. Robots are widely used in metallurgic al industry, machinery manufacture, light industry and atomic energy sectors.Can mimic some of the staff and arm motor function, a fixd procedure for the capture, handling objects or operating tools, automatic operation device. It can replace hum an labor in order to achieve the production of heavy mechanization and automation th at can operate in hazardous environments to protect the personal safety, which is wide ly used in machinery manufacturing, metallurgy, electronics, light industry and nuclea r power sectors. Mechanical hand tools or other equipment commonly used for additio nal devices, such as the automatic machines or automatic production line handling an d transmission of the workpiece, the replacement of cutting tools in machining centers , etc. generally do not have a separate control device. Some operating devices require direct manipulation by humans; such as the atomic energy sector performs household hazardous materials used in the master-slave manipulator is also often referred to as m echanical hand.Manipulator mainly by hand and sports institutions. Task of hand is holding the wor kpiece (or tool) components, according to grasping objects by shape, size, weight, mat erial and operational requirements of a variety of structural forms, such as clamp type, type and adsorption-based care such as holding. Sports organizations, so that the com pletion of a variety of hand rotation (swing), mobile or compound movements to achie ve the required action, to change the location of objects by grasping and posture. Robot is the automated production of a kind used in the process of crawling and mo ving piece features automatic device, which is mechanized and automated production process developed a new type of device. In recent years, as electronic technology, esp ecially computer extensive use of robot development and production of high-tech fiel ds has become a rapidly developed a new technology, which further promoted the dev elopment of robot, allowing robot to better achieved with the combination of mechani zation and automation. Robot can replace humans completed the risk of duplication of boring work, to reduce human labor intensity and improve labor productivity. Manipu lator has been applied more and more widely, in the machinery industry, it can be use d for parts assembly, work piece handling, loading and unloading, particularly in the a utomation of CNC machine tools, modular machine tools more commonly used. At pr esent, the robot has developed into a FMS flexible manufacturing systems and flexibl e manufacturing cell in an important component of the FMC. The machine tool equipment and machinery in hand together constitute a flexible manufacturing system or a f lexible manufacturing cell, it was adapted to small and medium volume production, y ou can save a huge amount of the work piece conveyor device, compact, and adaptabl e. When the work piece changes, flexible production system is very easy to change wi ll help enterprises to continuously update the marketable variety, improve product qua lity, and better adapt to market competition. At present, China's industrial robot techno logy and its engineering application level and comparable to foreign countries there is a certain distance, application and industrialization of the size of the low level of robo t research and development of a direct impact on raising the level of automation in Ch ina, from the economy, technical considerations are very necessary. Therefore, the stu dy of mechanical hand design is very meaningful.附件1：外文资料翻译译文机械手机械手是近几十年发展起来的一种高科技自动化生产设备。

中英文对照翻译最小化传感级别不确定性联合策略的机械手控制摘要：人形机器人的应用应该要求机器人的行为和举止表现得象人。

下面的决定和控制自己在很大程度上的不确定性并存在于获取信息感觉器官的非结构化动态环境中的软件计算方法人一样能想得到。

在机器人领域，关键问题之一是在感官数据中提取有用的知识，然后对信息以及感觉的不确定性划分为各个层次。

本文提出了一种基于广义融合杂交分类（人工神经网络的力量，论坛渔业局）已制定和申请验证的生成合成数据观测模型，以及从实际硬件机器人。

选择这个融合，主要的目标是根据内部（联合传感器）和外部（ Vision 摄像头）感觉信息最大限度地减少不确定性机器人操纵的任务。

目前已被广泛有效的一种方法论就是研究专门配置5个自由度的实验室机器人和模型模拟视觉控制的机械手。

在最近调查的主要不确定性的处理方法包括加权参数选择（几何融合），并指出经过训练在标准操纵机器人控制器的设计的神经网络是无法使用的。

这些方法在混合配置，大大减少了更快和更精确不同级别的机械手控制的不确定性，这中方法已经通过了严格的模拟仿真和试验。

关键词：传感器融合，频分双工，游离脂肪酸，人工神经网络，软计算，机械手，可重复性，准确性，协方差矩阵，不确定性，不确定性椭球。

1 引言各种各样的机器人的应用（工业，军事，科学，医药，社会福利，家庭和娱乐）已涌现了越来越多产品，它们操作范围大并呢那个在非结构化环境中运行 [ 3,12,15]。

在大多数情况下，如何认识环境正在发生变化且每个瞬间最优控制机器人的动作是至关重要的。

移动机器人也基本上都有定位和操作非常大的非结构化的动态环境和处理重大的不确定性的能力[ 1,9,19 ]。

每当机器人操作在随意性自然环境时，在给定的工作将做完的条件下总是存在着某种程度的不确定性。

这些条件可能，有时不同当给定的操作正在执行的时候。

导致这种不确定性的主要的原因是来自机器人的运动参数和各种确定任务信息的差异所引起的。

机器人发展英语作文English:As technology continues to advance, the development of robots has become increasingly prominent. From manufacturing industries to households, robots are being used in various fields to improve efficiency and productivity. With advancements in artificial intelligence, robots are able to perform more complex tasks and interact with humans in a more sophisticated manner. This has led to a growing interest in the field of robotics, with researchers and engineers constantly working on new innovations and improvements. While there are concerns about job displacement and ethical issues surrounding the use of robots, the benefits they bring in terms of precision, consistency, and safety cannot be denied. As robots continue to evolve and become more integrated into our daily lives, it is important for society to adapt and embrace this technological advancement.中文翻译:随着科技的不断进步，机器人的发展变得日益突出。

Robotics technology trendsBy : Jim Pinto, San Diego, CA. USAWhen it comes to robots, reality still lags science fiction. But, just because robots have not lived up to their promise in past decades does not mean that they will not arrive sooner or later. Indeed, the confluence of several advanced technologies is bringing the age of robotics ever nearer - smaller, cheaper, more practical and cost-effectiveBrawn, Bone & BrainThere are 3 aspects of any robot:∙Brawn – strength relating to physical payload that a robot can move.∙Bone – the physical structure of a robot relative to the work it does; this determines the size and weight of the robot in relation to its physical payload.∙Brain – robotic intelligence; what it can think and do independently; how much manual interaction is required.Because of the way robots have been pictured in science fiction, many people expect robots to be human-like in appearance. But in fact what a robot looks like is more related to the tasks or functions it performs. A lot of machines that look nothing like humans can clearly be classified as robots. And similarly, some human-looking robots are not much beyond mechanical mechanisms, or toys.Many early robots were big machines, with significant brawn and little else. Old hydraulically powered robots were relegated to tasks in the 3-D category – dull, dirty and dangerous. The technological advances since the first industry implementation have completely revised the capability, performance and strategic benefits of robots. For example, by the 1980s robots transitioned from being hydraulically powered to become electrically driven units. Accuracy and performance improved.Industrial robots already at workThe number of robots in the world today is approaching 1,000,000, with almost half that number in Japan and just 15% in the US. A couple of decades ago, 90% of robots were used in car manufacturing, typically on assembly lines doing a variety of repetitive tasks. Today only 50% are in automobile plants, with the other half spread out among other factories, laboratories, warehouses, energy plants, hospitals, and many other industries.Robots are used for assembling products, handling dangerous materials,spray-painting, cutting and polishing, inspection of products. The number of robots used in tasks as diverse as cleaning sewers, detecting bombs and performing intricate surgery is increasing steadily, and will continue to grow in coming years.Robot intelligenceEven with primitive intelligence, robots have demonstrated ability to generate good gains in factory productivity, efficiency and quality. Beyond that, some of the "smartest" robots are not in manufacturing; they are used as space explorers, remotely operated surgeons and even pets – like Sony's AIBO mechanical dog. In some ways, some of these other applications show what might be possible on production floors if manufacturers realize that industrial robots don't have to be bolted to the floor, or constrained by the limitations of yesterday's machinery concepts.With the rapidly increasing power of the microprocessor and artificial intelligence techniques, robots have dramatically increased their potential as flexible automation tools. The new surge of robotics is in applications demanding advanced intelligence. Robotic technology is converging with a wide variety of complementary technologies – machine vision, force sensing (touch), speech recognition and advanced mechanics. This results in exciting new levels of functionality for jobs that were never before considered practical for robots.The introduction of robots with integrated vision and touch dramatically changes the speed and efficiency of new production and delivery systems. Robots have become so accurate that they can be applied where manual operations are no longer a viable option. Semiconductor manufacturing is one example, where a consistent high levelof throughput and quality cannot be achieved with humans and simple mechanization. In addition, significant gains are achieved through enabling rapid product changeover and evolution that can't be matched with conventional hard tooling.Boosting CompetitivenessAs mentioned, robotic applications originated in the automotive industry. General Motors, with some 40-50,000 robots, continues to utilize and develop new approaches. The ability to bring more intelligence to robots is now providing significant new strategic options. Automobile prices have actually declined over the last two to three years, so the only way that manufacturers can continue to generate profits is to cut structural and production costs.When plants are converted to new automobile models, hundreds of millions of dollars are typically put into the facility. The focus of robotic manufacturing technology is to minimize the capital investment by increasing flexibility. New robot applications are being found for operations that are already automated with dedicated equipment. Robot flexibility allows those same automated operations to be performed more consistently, with inexpensive equipment and with significant cost advantages.Robotic AssistanceA key robotics growth arena is Intelligent Assist Devices (IAD) – operators manipulate a robot as though it were a bionic extension of their own limbs with increased reach and strength. This is robotics technology – not replacements for humans or robots, but rather a new class of ergonomic assist products that helpshuman partners in a wide variety of ways, including power assist, motion guidance, line tracking and process automation.IAD’s use robotics t echnology to help production people to handle parts and payloads – more, heavier, better, faster, with less strain. Using a human-machine interface, the operator and IAD work in tandem to optimize lifting, guiding and positioning movements. Sensors, computer power and control algorithms translate the operator's hand movements into super human lifting power.New robot configurationsAs the technology and economic implications of Moore's law continue to shift computing power and price, we should expect more innovations, more cost-effective robot configurations, more applications beyond the traditional “dumb-waiter” service emphasis.The biggest change in industrial robots is that they will evolve into a broader variety of structures and mechanisms. In many cases, configurations that evolve into new automation systems won't be immediately recognizable as robots. For example, robots that automate semiconductor manufacturing already look quite different from those used in automotive plants.We will see the day when there are more of these programmable tooling kinds of robots than all of the traditional robots that exist in the world today. There is an enormous sea change coming; the potential is significant because soon robots will offer not only improved cost-effectiveness, but also advantages and operations that have never been possible before.Envisioning VisionDespite the wishes of robot researchers to emulate human appearance and intelligence, that simply hasn't happened. Most robots still can't see – versatile and rapid objectrecognition is still not quite attainable. And there are very few examples of bipedal, upright walking robots such as Honda’s P3, mostly used for research or sample demonstrations.A relatively small number of industrial robots are integrated with machine vision systems – which is why it's called machine vision rather than robot vision. The early machine vision adopters paid very high prices, because of the technical expertise needed to “tweak” such systems. For example, in the mid-1980s, a flexible manufacturing system from Cincinnati Milacron included a $900,000 vision guidance system. By 1998 average prices had fallen to $40,000, and prices continued to decline.Today, simple pattern matching vision sensors can be purchased for under $2,000 from Cognex, Omron and others. The price reductions reflect today's reduced computing costs, and the focused development of vision systems for specific jobs such as inspection.Robots already in use everywhereSales of industrial robots have risen to record levels and they have huge, untapped potential for domestic chores like mowing the lawn and vacuuming the carpet. Last year 3,000 underwater robots, 2,300 demolition robots and 1,600 surgical robots were in operation. A big increase is predicted for domestic robots for vacuum cleaning and lawn mowing, increasing from 12,500 in 2000 to almost 500,000 by the end of 2004. IBot’s Roomba floor cleaning robot is now available at under $200.00.In the wake of recent anthrax scares, robots are increasingly used in postal sorting applications. Indeed, there is huge potential to mechanize the US postal service. Some 1,000 robots were installed last year to sort parcels and the US postal service has estimated that it has the potential to use up to 80,000 robots for sorting.Look around at the “robots” around us today: automated gas pumps, bank ATMs,self-service checkout lanes – machines that are already replacing many service jobs.Fast-forward another few decades. It doesn't require a great leap of faith to envision how advances in image processing, microprocessor speed and human-simulation could lead to the automation of most boring, low-intelligence, low-paying jobs.Marshall Brain (yes, that's his name) founder of has written a couple of interesting essays about robotics in the future, well worth reading. He feels that it is quite plausible that over the next 40 years robots will displace most human jobs. According to Brain's projections, in his essay "Robotic Nation", humanoid robots will be widely available by 2030. They will replace jobs currently filled by people for work such as fast-food service, housecleaning and retail sales. Unless ways are found to compensate for these lost jobs, Brain estimates that more than 50% of Americans could be unemployed by 2055 – replaced by robots.New robot applications aboundAs robot intelligence increases, and as sensors, actuators and operating mechanisms become more sophisticated, other applications are now multiplying. There are now thousands of underwater robots, demolition robots and even robots used inlong-distance surgery.Dozens of experimental search-and-rescue robots scoured the wreckage of the World Trade Center's collapsed twin towers. Teams of robotics experts were at Ground Zero operating experimental robots to probe the rubble and locate bodies. During the war in Afghanistan, robots were being used by the US military as tools for combat. They were sent into caves, buildings or other dark areas ahead of troops to help prevent casualties.A giant walking robot is used to harvests forests, moving on six articulated legs, advancing forward and backward, sideways and diagonally. It can also turn in place and step over obstacles.At UC Berkeley, a tiny robot called Micromechanical Flying Insect has wings that flap with a rhythm and precision matched only by natural equivalents. The goal is to develop tiny, nimble devices that can, for example, surreptitiously spy on enemy troops, explore the surface of Mars or safely monitor dangerous chemical spills.Robotics – an exciting new development arenaThe typical Automation techie has knowledge and experience in instruments, PLCs, computers, displays, controls, sensors, valves, actuators, data-transmission, wireless, networking, etc. These are exactly the key requirements for development of robots and robotic systems. During this time of economic recession, Robotics can surely be a new arena of exciting and rewarding business development.机器人技术发展趋势作者：Jim Pinto，加利福利亚州圣迭亚哥·美国谈到机器人，现实仍落后于科幻小说。

附录About Modenr Industrial Manipulayor Robot is a type of mechantronics equipment which synthesizes the last research achievement of engine and precision engine, micro-electronics and computer, automation control and drive, sensor and message dispose and artificial intelligence and so on. With the development of economic and the demand for automation control, robot technology is developed quickly and all types of the robots products are come into being. The practicality use of robot not only solves the problems which are difficult to operate for human being, but also advances the industrial automation program. Modern industrial robots are true marvels of engineering. A robot the size of a person can easily carry a load over one hundred pounds and move it very quickly with a repeatability of 0.006inches. Furthermore these robots can do that 24hours a day for years on end with no failures whatsoever. Though they are reprogrammable, in many applications they are programmed once and then repeat that exact same task for years.At present, the research and development of robot involves several kinds of technology and the robot system configuration is so complex that the cost at large is high which to a certain extent limit the robot abroad use. To development economic practicality and high reliability robot system will be value to robot social application and economy development. With he rapidprogress with the control economy and expanding of the modern cities, the let of sewage is increasing quickly; with the development of modern technology and the enhancement of consciousness about environment reserve, more and more people realized the importance and urgent of sewage disposal. Active bacteria method is an effective technique for sewage disposal. The abundance requirement for lacunaris plastic makes it is a consequent for plastic producing with automation and high productivity. Therefore, it is very necessary to design a manipulator that can automatically fulfill the plastic holding. With the analysis of the problems in the design of the plastic holding manipulator and synthesizing the robot research and development condition in recent years, a economic scheme is concluded on the basis of the analysis of mechanical configuration, transform system, drive device and control system and guided by the idea of the characteristic and complex of mechanical configuration, electronic, software and hardware. In this article, the mechanical configuration combines the character of direction coordinate which can improve the stability and operation flexibility of the system. The main function of the transmission mechanism is to transmit power to implement department and complete the necessary movement. In this transmission structure, the screw transmission mechanism transmits the rotary motion into linear motion. Worm gear can give vary transmission ratio. Both of the transmission mechanisms have a characteristic of compact structure. The design of drive system often is limited by the environment condition and the factor of costand technical lever. The step motor can receive digital signal directly and has the ability to response outer environment immediately and has no accumulation error, which often is used in driving system. In this driving system, open-loop control system is composed of stepping motor, which can satisfy the demand not only for control precision but also for the target of economic and practicality. On this basis, the analysis of stepping motor in power calculating and style selecting is also given. The analysis of kinematics and dynamics for object holding manipulator is given in completing the design of mechanical structure and drive system.Current industrial approaches to robot arm control treat each joint of the robot arm as a simple joint servomechanism. The servomechanism approach models the varying dynamics of a manipulator inadequately because it neglects the motion and configuration of the whole arm mechanism. These changes in the parameters of the controlled system sometimes are significant enough to render conventional feedback control strategies ineffective. The result is reduced servo response speed and damping, limiting the precision and speed of the end-effecter and making it appropriate only for limited-precision tasks. Manipulators controlled in this manner move at slow speeds with unnecessary vibrations. Any significant performance gain in this and other areas of robot arm control require the consideration of more efficient dynamic models, sophisticated control approaches, and the use of dedicated computer architectures and parallel processing techniques.In the industrial production and other fields, people often endangered by such factors as high temperature, corrode, poisonous gas and so forth at work, which have increased labor intensity and even jeopardized the life sometimes. The corresponding problems are solved since the robot arm comes out. The arms can catch, put and carry objects, and its movements are flexible and diversified. It applies to medium and small-scale automated production in which production varieties can be switched. And it is widely used on soft automatic line. The robot arms are generally made by withstand high temperatures, resist corrosion of materials to adapt to the harsh environment. So they reduced the labor intensity of the workers significantly and raised work efficiency. The robot arm is an important component of industrial robot, and it can be called industrial robots on many occasions. Industrial robot is set machinery, electronics, control, computers, sensors, artificial intelligence and other advanced technologies in the integration of multidisciplinary important modern manufacturing equipment. Widely using industrial robots, not only can improve product quality and production, but also is of great significance for physical security protection, improvement of the environment for labor, reducing labor intensity, improvement of labor productivity, raw material consumption savings and lowering production costs.There are such mechanical components as ball footbridge, slides, air control mechanical hand and so on in the design. A programmable controller, a programming device, stepping motors, stepping motors drives, direct currentmotors, sensors, switch power supply, an electromagnetism valve and control desk are used in electrical connection.Robot is the automated production of a kind used in the pr ocess of crawling and moving piece features automatic device, wh ich is mechanized and automated production process developed a n ew type of device. In recent years, as electronic technology, e specially computer extensive use of robot development and product ion of hightech fields has become a rapidly developed a new te chnology, which further promoted the development of robot, allowi ng robot to better achieved with the combination of mechanizatio n and automation. Robot can replace humans completed the risk o f duplication of boring work, to reduce human labor intensity a nd improve labor productivity. Manipulator has been applied more and more widely, in the machinery industry, it can be used f or parts assembly, work piece handling, loading and unloading, p articularly in the automation of CNC machine tools, modular mach ine tools more commonly used. At present, the robot has develop ed into a FMS flexible manufacturing systems and flexible manufa cturing cell in an important component of the FMC. The machine tool equipment and machinery in hand together constitute a fle xible manufacturing system or a flexible manufacturing cell, it was adapted to small and medium volume production, you can savea huge amount of the work piece conveyor device, compact, and adaptable. When the work piece changes, flexible production sys tem is very easy to change will help enterprises to continuousl y update the marketable variety, improve product quality, and be tter adapt to market competition. At present, China's industrial robot technology and its engineering application level and comp arable to foreign countries there is a certain distance, applica tion and industrialization of the size of the low level of rob ot research and development of a direct impact on raising the level of automation in China, from the economy, technical consid erations are very necessary. Therefore, the study of mechanical hand design is very meaningful.关于现代工业机械手机器人是典型的机电一体化装置，它综合运用了机械与精密机械、微电子与计算机、自动控制与驱动、传感器与信息处理以及人工智能等多学科的最新研究成果，随着经济技术的发展和各行各业对自动化程度要求的提高，机器人技术得到了迅速发展，出现了各种各样的机器人产品。

机器人外文翻译(中英文翻译)机器人外文翻译(中英文翻译)With the rapid development of technology, the use of robots has become increasingly prevalent in various industries. Robots are now commonly employed to perform tasks that are dangerous, repetitive, or require a high level of precision. However, in order for robots to effectively communicate with humans and fulfill their intended functions, accurate translation between different languages is crucial. In this article, we will explore the importance of machine translation in enabling robots to perform translation tasks, as well as discuss current advancements and challenges in this field.1. IntroductionMachine translation refers to the use of computer algorithms to automatically translate text or speech from one language to another. The ultimate goal of machine translation is to produce translations that are as accurate and natural as those generated by human translators. In the context of robots, machine translation plays a vital role in allowing them to understand and respond to human commands, as well as facilitating communication between robots of different origins.2. Advancements in Machine TranslationThe field of machine translation has experienced significant advancements in recent years, thanks to breakthroughs in artificial intelligence and deep learning. These advancements have led to the development of neural machine translation (NMT) systems, which have greatly improved translation quality. NMT models operate by analyzinglarge amounts of bilingual data, allowing them to learn the syntactic and semantic structures of different languages. As a result, NMT systems are capable of providing more accurate translations compared to traditional rule-based or statistical machine translation approaches.3. Challenges in Machine Translation for RobotsAlthough the advancements in machine translation have greatly improved translation quality, there are still challenges that need to be addressed when applying machine translation to robots. One prominent challenge is the variability of language use, including slang, idioms, and cultural references. These nuances can pose difficulties for machine translation systems, as they often require a deep understanding of the context and cultural background. Researchers are currently working on developing techniques to enhance the ability of machine translation systems to handle such linguistic variations.Another challenge is the real-time requirement of translation in a robotic setting. Robots often need to process and translate information on the fly, and any delay in translation can affect the overall performance and efficiency of the robot. Optimizing translation speed without sacrificing translation quality is an ongoing challenge for researchers in the field.4. Applications of Robot TranslationThe ability for robots to translate languages opens up a wide range of applications in various industries. One application is in the field of customer service, where robots can assist customers in multiple languages, providing support and information. Another application is in healthcare settings, where robots can act as interpreters between healthcare professionals and patientswho may speak different languages. Moreover, in international business and diplomacy, robots equipped with translation capabilities can bridge language barriers and facilitate effective communication between parties.5. ConclusionIn conclusion, machine translation plays a crucial role in enabling robots to effectively communicate with humans and fulfill their intended functions. The advancements in neural machine translation have greatly improved translation quality, but challenges such as language variability and real-time translation requirements still exist. With continuous research and innovation, the future of machine translation for robots holds great potential in various industries, revolutionizing the way we communicate and interact with technology.。

外文原文Introduction to Industrial RobotsIndustrial robets became a reality in the early 1960’s when Joseph Engelberger and George Devol teamed up to form a robotics company they called “Unimation”.Engelberger and Devol were not the first to dream of machines that could perform the unskilled, repetitive jobs in manufacturing. The first use of the word “robots” was by the Czechoslovakian philosopher and playwright Karel Capek in his play R.U.R.(Rossum’s Universal Robot). The word “robot” in Czech means “worker” or “slave.” The play was written in 1922.In Capek’s play , Rossum and his son discover the chemical formula for artificial protoplasm. Protoplasm forms the very basis of life.With their compound,Rossum and his son set out to make a robot.Rossum and his son spend 20 years forming the protoplasm into a robot. After 20 years the Rossums look at what they have created and say, “It’s absurd to spend twenty years making a man if we can’t make him quicker than nature, you might as w ell shut up shop.”The young Rossum goes back to work eliminating organs he considers unnecessary for the ideal worker. The young Rossum says, “A man is something that feels happy , plays piano ,likes going for a walk, and in fact wants to do a whole lot of things that are unnecessary … but a working machine must not play piano, must not feel happy, must not do a whole lot of other things. Everything that doesn’t contribute directly to the progress of work should be eliminated.”A half century later, engi neers began building Rossum’s robot, not out of artificial protoplasm, but of silicon, hydraulics, pneumatics, and electric motors. Robots that were dreamed of by Capek in 1922, that work but do not feel, that perform unhuman or subhuman, jobs in manufacturing plants, are available and are in operation around the world.The modern robot lacks feeling and emotions just as Rossum’s son thought it should. It can only respond to simple “yes/no” questions. The moderrn robot is normally bolted to the floor. It has one arm and one hand. It is deaf, blind, and dumb. In spite of all of these handicaps, the modern robot performs its assigned task hour after hour without boredom or complaint.A robot is not simply another automated machine. Automation began during the industrial revolution with machines that performed jobs that formerly had been done by human workers. Such a machine, however , can do only the specific job for which it was designed, whereas a robot can perform a variety of jobs.A robot must have an arm. The arm must be able to duplicate the movements of a human worker in loading and unloading other automated machines, spraying paint, welding, and performing hundreds of other jobs that cannot be easily done with conventional automated machines.DEFINITION OF A ROBOTThe Robot Industries Association(RIA) has published a definition for robots in an attempt to clarify which machines are simply automated machines and which machines are truly robots. The RIA definition is as follows:“A robot is a reprogrammabl e multifunctional manipulator designed to move material, parts, tools, or specialized devices through variable programmed motions for the performance of a variety of tasks.”This definition, which is more extensive than the one in the RIA glossary at the end of this book, is an excellent definition of a robot. We will look at this definition, one phrase at a time, so as to understand which machines are in fact robots and which machines are little more than specialized automation.First, a robot is a “reprogrammable multifunctional manipulator.” In this phrase RIA tells us that a robot can be taught (“reprogrammed”) to do more than one job by changing the informaion stored in its memory. A robot can be reprogrammed to load and unload machines, weld, and do ma ny other jobs (“multifunctional”). A robot is a“manipulator”. A manipulator is an arm( or hand ) that can pick up or move things. At this point we know that a robot is an arm that can be taught to do different jobs.The definition goes on to say that a ro bot is “designed to move material, parts, tools, or specialized devices.” Material includes wood,steel, plastic, cardboard… anything that is used in the manufacture of a product.A robot can also handle parts that have been manufactured. For example, a robot can load a piece of steel into an automatic lathe and unload a finished part out of the lathe.In addition to handling material and parts, a robot can be fitted with tools such as grinders, buffers, screwdrivers, and welding torches to perform useful work.Robots can also be fitted with specialized instruments or devices to do special jobs in a manufacturing plant. Robots can be fitted with television cameras for inspection of parts or products. They can be fitted with lasers to accurately mearure the size of parts being manufactured.The RIA definition closes with the phrase,”…through variable programmed motions for the performance of a variety of tasks.” This phrase emphasizes the fact that a robot can do many different jobs in a manufacturing plant. The variety of jobs that a robot can do is limited only by the creativity of the application engineer.JOBS FOR ROBOTSJobs performed by robots can be divided into two major categories:hazardous jobs and repetitive jobs.Hazardous JobsMany applications of robots are in jobs that are hazardous to humans. Such jobs may be considered hazardous because of toxic fumes, the weight of the material being handled, the temperature of the material being handled, the danger of working near rotating or press machinery, or environments containing high levels of radiation. Repetitive JobsIn addition to taking over hazardous jobs, robots are well suited to doingextremely repetitive jobs that must be done in manufacturing plants.many jobs in manufacturing plants require a person to act more like a machine than like a human. The job may be to pick a piece up from here and place it there. The same job is done hundreds of times each day. The job requires little or no judgment and little or no skill. This is not said as a criticism of the person who does the job , but is intended simply to point out that many of these jobs exist in industry and must be done to complete the manufacture of products. A robot can be placed at such a work station and can perform the job admirably without complaining or experiencing the fatigue and boredom normally associated with such a job.Although robots eliminate some jobs in industry, they normally eliminate jobs that humans should never have been asked to do. Machines should perform as machines doing machine jobs, and humans should be placed in jobs that require the use of their ability,creativity, and special skills.POTENTIAL FOR INCREASED PRODUCTIVITYIn addition to removing people from jobs they should not have been placed in, robots offer companies the opportunity of achieving increased productivity. When robots are placed in repetitive jobs they continue to operate at their programmed pace without fatigue. Robots do not take either scheduled or unscheduled breaks from the job. The increase in productivity can result in at least 25% more good parts being produced in an eight-hour shift. This increase in productivity increases the company's profits, which can be reinvested in additional plants and equipment. This increase in productivity results in more jobs in other departments in the plant. With more parts being produced, additional people are needed to deliver the raw materials to the plant, to complete the assembly of the finished products, to sell the finished products, and to deliver the products to their destinations.ROBOT SPEEDAlthough robots increase productivity in a manufacturing plant, they are notexceptionally fast. At present, robots normally operate at or near the speed of a human operator. Every major move of a robot normally takes approximately one second. For a robot to pick up a piece of steel from a conveyor and load it into a lathe may require ten different moves taking as much as ten seconds. A human operator can do the same job in the same amount of time . The increase in productivity is a result of the consistency of operation. As the human operator repeats the same job over and over during the workday, he or she begins to slow down. The robot continues to operate at its programmed speed and therefore completes more parts during the workday.Custom-built automated machines can be built to do the same jobs that robots do. An automated machine can do the same loading operation in less than half the time required by a robot or a human operator. The problem with designing a special machine is that such a machine can perform only the specific job for which it was built. If any change is made in the job, the machine must be completely rebuilt, or the machine must be scrapped and a new machine designed and built. A robot, on the other hand, could be reprogrammed and could start doing the new job the same day.Custom-built automated machines still have their place in industry. If a company knows that a job will not change for many years, the faster custom-built machine is still a good choice.Other jobs in factories cannot be done easily with custom-built machinery. For these applications a robot may be a good choice. An example of such an application is spray painting. One company made cabinets for the electronics industry. They made cabinets of many different sizes, all of which needed painting. It was determined that it was not economical for the company to build special spray painting machines for each of the different sizes of enclosures that were being built. Until robots were developed, the company had no choice but to spray the various enclosures by hand.Spray painting is a hazardous job , because the fumes from many paints are both toxic and explosive. A robot is now doing the job of spraying paint on the enclosures.A robot has been “taught” to spray all the different sizes of enclosures that the company builds. In addition, the robot can operate in the toxic environment of the spray booth without any concern for the long-term effect the fumes might have on aperson working in the booth.FLEXIBLE AUTOMATIONRobots have another advantage: they can be taught to do different jobs in the manufacturing plant. If a robot was originally purchased to load and unload a punch press and the job is no longer needed due to a change in product design, the robot can be moved to another job in the plant. For example, the robot could be moved to the end of the assembly operation and be used to unload the finished enclosures from a conveyor and load them onto a pallet for shipment.ACCURACY AND REPEATABILITYOne very important characteristic of any robot is the accuracy with which it can perform its task. When the robot is programmed to perform a specific task, it is led to specific points and programmed to remember the locations of those points. After programming has been completed, the robot is switched to “run” and the program is executed. Unfortunately, the robot will not go to the exact location of any programmed point. For example, the robot may miss the exact point by 0.025 in. If 0.025 in. is the greatest error by which the robot misses any point- during the first execution of the program, the robot is said to have an accuracy of 0.025 in.In addition to accuracy , we are also concerned with the robot’s repeatability. The repeatability of a robot is a measure of how closely it returns to its programmed points every time the program is executed. Say , for example, that the robot misses a programmed point by 0.025 in. the first time the program is executed and that, during the next execution of the program, the robot misses the point it reached during the previous cycle by 0.010 in. Although the robot is a total of 0.035 in. from the original programmed point, its accuracy is 0.025 in. and its repeatability is 0.010 in.THE MAJOR PARTS OF A ROBOTThe major parts of a robot are the manipulator, the power supply, and the controller.The manipulator is used to pick up material, parts, or special tools used in manufacturing. The power supply suppplies the power to move the manipulator. The controller controls the power supply so that the manipulator can be taught to perform its task.外文翻译工业机器人的介绍20世纪60年代当约瑟夫和乔治合作创立了名为Unimation的机器公司，工业机器人便成为了一个事实。

中英文翻译(文档含英文原文和中文翻译)外文文献：Space Robot Path Planningfor Collision AvoidanceAbstract — This paper deals with a path planning of space robot which includes a collision avoidance algorithm. For the future space robot operation, autonomous and self-contained path planning is mandatory to capture a target without the aid of ground station. Especially the collision avoidance with target itself must be always considered. Once the location, shape and grasp point of the target are identified, those will be expressed in the configuration space. And in this paper a potential method.Laplace potential function is applied to obtain the path in the configuration space in order to avoid so-called deadlock phenomenon. Improvement on the generation of the path has been observed by applying path smoothing method, which utilizes the spline function interpolation. This reduces the computational load and generates the smooth path of the space robot. The validity of this approach is shown by a few numerical simulations.Key Words—Space Robot, Path Planning, Collision Avoidance, Potential Function, Spline InterpolationI. INTRODUCTIONIn the future space development, the space robot and its autonomy will be key features of thespace technology. The space robot will play roles to construct space structures and perform inspections and maintenance of spacecrafts. These operations are expected to be performed in an autonomous.In the above space robot operations, a basic and important task is to capture free flying targets on orbit by the robotic arm. For the safe capturing operation, it will be required to move the arm from initial posture to final posture without collisions with the target.The configuration space and artificial potential methods are often applied to the operation planning of the usual robot. This enables the robot arm to evade the obstacle and to move toward the target. Khatib proposed a motion planning method, in which between each link of the robot and the obstacle the repulsive potential is defined and between the end-effecter of the robot and the goal the attractive potential is defined and by summing both of the potentials and using the gradient of this potential field the path is generated. This method is advantageous by its simplicity and applicability for real-time operation. However there might be points at which the repulsive force and the attractive force are equal and this will lead to the so-called deadlock.In order to resolve the above issue, a few methods are proposed where the solution of Laplace equation is utilized. This method assures the potential fields without the local minimum, i.e., no deadlock. In this method by numerical computation Laplace equation will be solved and generates potential field. The potential field is divided into small cells and on each node the discrete value of the potential will be specified.In this paper for the elimination of the above defects, spline interpolation technique is proposed. The nodal point which is given as a point of path will be defined to be a part of smoothed spline function. And numerical simulations are conducted for the path planning of the space robot to capture the target, in which the potential by solving the Laplace equation is applied and generates the smooth and continuous path by the spline interpolation from the initial to the final posture.II. ROBOT MODELThe model of space robot is illustrated in Fig.1.The robot is mounted on a spacecraft and has two rotary joints which allow the in-plane motion of the end-effecter. In this case we have an additional freedom of the spacecraft attitude angle and this will be considered the additional rotary joint. This means that the space robot isthree linked with 3 DOF (Degree Of Freedom). The length of each link and the angle of each rotary joint are given by i l and i (i = 1,2,3) , respectively. In order to simplify the discussions a few assumptions are made in this paper:-the motion of the space robot is in-plane,i.e., two dimensional one.-effect of robot arm motion to the spacecraft attitude is negligible.-robot motion is given by the relation of static geometry and not explicitly depending on time. -the target satellite is inertially stabilized.In general in-plane motion and out-of-plane motion will be separately performed. So we are able to assume the above first one without loss of generality. The second assumption derives from the comparison of the ratio of mass between the robot arm and the spacecraft body. With respect to the third assumption we focus on generating the path planning of the robot and this is basically given by the static nature of geometry relationship and is therefore not depending on the time explicitly. The last one means the satellite is cooperative.Fig.1 Model of Two-link Space RobotIII. PATH PLANNING GALGORITHMA. Laplace Potential GuidanceThe solution of the Laplace equation (1) is called a Harmonic potential function, and its and minimum values take place only on the boundary. In the robot path generation the boundary means obstacle and goal. Therefore inside the region where the potential is defined, no local minimum takes place except the goal. This eliminates the deadlock phenomenon for path generation.2n22i 1i 0x =∂∅∅==∂∑∇ （1） The Laplace equation can be solved numerically. We define two dimensional Laplace equation as below:22220x y∂∅∂∅+=∂∂ （2） And this will be converted into the difference equation and then solved by Gauss -Seidel method. In equation (2) if we take the central difference formula for second derivatives, the following equation will be obtained:2222220x y(x x,y )2(x,y )(x x,y )x(x,y y )2(x,y )(x,y y )y ∆∆∂∅∂∅+=∂∂∅+∆-∅+∅-∆⇒∅+∆-∅+∅-∆+ （3） where x ∆，y ∆ are the step (cell) sizes between adjacent nodes for each x , y direction. If the step size is assumed equal and the following notation is used:i 1,j (x x,y )+∅+∆=∅Then equation (3) is expressed in the following manner:1,1,,1,1,0i j i j i j i j i j +-+-∅+∅+∅+∅-4∅= （4）And as a result, two dimensional Laplace equation will be converted into the equation (5) as below:i,j i 1,j i 1,j i,j 1i,j 114+-+-∅=(∅+∅+∅+∅) （5） In the same manner as in the three dimensional case, the difference equation for the three dimensional Laplace equation will be easily obtained by the following:i,j ,k i 1,j ,k i 1,j ,k i,j 1,k i,j 1,k i,j ,k 1i,j ,k 116+-+-+-∅=(∅+∅+∅+∅+∅+∅) （6） In order to solve the above equations we apply Gauss-Seidel method and have equations as follows:n 1n n 1n n 1i,j i 1,j i 1,j i,j 1i,j 114++++-+-∅=(∅+∅+∅+∅) （7）where 1,n i j +∅ is the computational result from the ( n +1 )-th iterative calculations of the potential.In the above computations, as the boundary conditions, a certain positive number 0∅ is defined for the obstacle and 0 for the goal. And as the initial conditions the same number 0∅ is also given for all of the free nodes. By this approach during iterative computations the value of the boundary nodes will not change and the values only for free nodes will be varying. Applying the same potential values as the obstacle and in accordance with the iterative computational process, the small potential around the goal will be gradually propagating like surrounding the obstacle. The potential field will be built based on the above procedure.Using the above potential field from 4 nodal points adjacent to the node on which the space robot exists, the smallest node is selected for the point to move to. This procedure finally leads the space robot to the goal without collision.B . Spline InterpolationThe path given by the above approach does not assure the smoothly connected one. And if the goal is not given on the nodal point, we have to partition the cells into much more smaller cells. This will increase the computational load and time.In order to eliminate the above drawbacks we propose the utilization of spline interpolation technique. By assigning the nodal points given by the solution to via points on the path, we try to obtain the smoothly connected path with accurate initial and final points.In this paper the cubic spline was applied by using MATLAB command.C. Configuration SpaceWhen we apply the Laplace potential, the path search is assured only in the case where the robot is expressed to be a point in the searching space. The configuration space(C-Space), where the robot is expressed as a point, is used for the path search. To convert the real space into the C-Space the calculation to judge the condition of collision is performed and if the collision exists, the corresponding point in the C-space is regarded as the obstacle. In this paper when the potential field was generated, the conditions of all the points in the real space, corresponding to all the nodes, were calculated. The judgment of intersection between a segment constituting the robot arm and a segment constituting the obstacle at each node was made and if the intersection takes place, this node is treated as the obstacle in the C-Space.IV.NUMERICAL SIMULATIONSBased on the above approach the path planning for capturing a target satellite was examined using a space robot model. In this paper we assume the space robot with two dimensional and 2 DOF robotic arm as shown in Fig.1.The length of each link is given as follows:l 1 =1.4[m ], l 2 = 2.0[m ], l 3 = 2.0[m ] ,and the target satellite was assumed 1m square. The grasp handle, 0.1 m square, was located at a center of one side of the target. So this handle is a goal of the path.Let us explain the geometrical relation between the space robot and the target satellite. When we consider the operation after capturing the target, it is desirable for the space robot to have the large manipulability. Therefore in this paper the end-effecter will reach the target when the manipulability is maximized. In the 3DOF case, not depending on the spacecraft body attitude, the manipulability is measured by 2,3θθ. And if we assume the end-effector of the space robot should be vertical to the target, then all of the joints angles are predetermined as follows:123160.7,32.8,76.5o o o θθθ===As all the joints angles are determined, the relative position between the spacecraft and the target is also decided uniquely. If the spacecraft is assumed to locate at the origin of the inertial frame (0, 0), the goal is given by (-3.27, -2.00) in the above case. Based on these preparations, we can search the path to the goal by moving the arm in the configuration space.Two simulations for path planning were carried out and the results are shown below.A. 2 DOF RobotIn order to simplify the situation, the attitude angle(Link 1 joint angle) is assumed to coincide with the desirable angle from the beginning. The coordinate system was assumed as shown in Fig.2.1θ was taken into consideration for the calculation of the initial condition of the Link 2 and its goal angles:Innitial condition:2364.3,90o θθο=-=Goal condition: 23166.5,76.5o θθο=-=In this case the potential field was computed for the C-Space with 180 segments. Fig.3 shows the C-Space and the hatched large portion in the center is given by the obstacle mapped by the spacecraft body. The left side portion is a mapping of the target satellite. Fig.4 shows a generated path and this was spline-interpolated curve by using alternate points of discrete data for smoothing .Fig.3 2 DOF C-SpaceFig.4 Path in C-Space(2 DOF)When we consider the rotation of spacecraft body, -180 degrees are equal to +180 degrees and, then, the state over -180 degrees will be started from +180 degrees and again back to the C-Space. For this reason the periodic boundary condition was applied in order to assure the continuity of the rotation. For the simplicity to look at the path, the mapped volume by the spacecraft body was omitted. Also for the simplicity of the path expression the chart which hasdirection was illustrated. From this figure it is easily the connection of -180 degrees in the1seen that over -180 degrees the path is going toward the goal C. B and C are the same goal point.V. CONCLUSIONIn this paper a path generation method for capturing a target satellite was proposed. And its applicability was demonstrated by numerical simulations. By using interpolation technique the computational load will be decreased and smoothed path will be available. Further research will be recommended to incorporate the attitude motion of the spacecraft body affected by arm motion.中文译文：空间机器人避碰路径规划摘要：本文论述的是空间机器人路径规划，这种规划主要运用的是避碰算法。

中英文对照资料外文翻译文献机器人技术发展趋势谈到机器人，现实仍落后于科幻小说。

但是，仅仅因为机器人在过去的几十年没有实现它们的承诺，并不意味着机器人的时代不会到来，或早或晚。

事实上，多种先进技术的影响已经使得机器人的时代变得更近——更小、更便宜、更实用和更具成本效益。

肌肉、骨骼和大脑任何一个机器人都有三方面：·肌肉——有效联系有关物理荷载以便于机器人运动。

·骨骼——一个机器人的物理结构取决于它所做的工作；它的尺寸大小和重量则取决于它的物理荷载。

·大脑——机器人智能；它能独立思考和做什么；需要多少人工互动。

由于机器人在科幻世界中所被描绘过的方式，很多人希望机器人在外型上与人类相似。

但事实上，机器人的外形更多地取决于它所做的工作或具备的功能。

很多一点儿也不像人的机器也被清楚地归为机器人。

同样，很多看起来像人的机器却还是仅仅属于机械结构和玩具。

很多早期的机器人是除了有很大力气而毫无其他功能的大型机器。

老式的液压动力机器人已经被用来执行3-D任务即平淡、肮脏和危险的任务。

由于第一产业技术的进步，完全彻底地改进了机器人的性能、业绩和战略利益。

比如，20世纪80年代，机器人开始从液压动力转换成为电动单位。

精度和性能也提高了。

工业机器人已经在工作时至今日，全世界机器人的数量已经接近100万，其中超过半数的机器人在日本，而仅仅只有15%在美国。

几十年前，90%的机器人是服务于汽车生产行业，通常用于做大量重复的工作。

现在，只有50%的机器人用于汽车制造业，而另一半分布于工厂、实验室、仓库、发电站、医院和其他的行业。

机器人用于产品装配、危险物品处理、油漆喷雾、抛光、产品的检验。

用于清洗下水道，探测炸弹和执行复杂手术的各种任务的机器人数量正在稳步增加，在未来几年内将继续增长。

机器人智能即使是原始的智力，机器人已经被证明了在生产力、效率和质量方面都能够创造良好的效益。

除此之外，一些“最聪明的”机器人没有用于制造业；它们被用于太空探险、外科手术遥控，甚至于宠物，比如索尼的AIBO电子狗。

Cooperative Mobile Robotics: Antecedents and DirectionsY. UNY CAOComputer Science Department, University of California, Los Angeles, CA 90024-1596ALEX S. FUKUNAGAJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109-8099ANDREW B. KAHNGComputer Science Department, University of California, Los Angeles, CA 90024-1596Editors: R.C. Arkin and G.A. BekeyAbstract. There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.Keywords: cooperative robotics, swarm intelligence, distributed robotics, artificial intelligence, mobile robots, multiagent systems1. PreliminariesThere has been much recent activity toward achieving systems of multiple mobile robots engaged in collective behavior. Such systems are of interest for several reasons:•tasks may be inherently too complex (or im-possible) for a single robot to accomplish, or performance benefits can be gained from using multiple robots;•building and using several simple robots can be easier, cheaper, more flexible and more fault-tolerant than having a single powerful robot foreach separate task; and•the constructive, synthetic approach inherent in cooperative mobile robotics can possibly∗This is an expanded version of a paper which originally appeared in the proceedings of the 1995 IEEE/RSJ IROS conference. yield insights into fundamental problems in the social sciences (organization theory, economics, cognitive psychology), and life sciences (theoretical biology, animal ethology).The study of multiple-robot systems naturally extends research on single-robot systems, butis also a discipline unto itself: multiple-robot systems can accomplish tasks that no single robot can accomplish, since ultimately a single robot, no matter how capable, is spatially limited. Multiple-robot systems are also different from other distributed systems because of their implicit “real-world” environment, which is presumably more difficult to model and reason about than traditional components of distributed system environments (i.e., computers, databases, networks).The term collective behavior generically denotes any behavior of agents in a system having more than one agent. the subject of the present survey, is a subclass of collective behavior that is characterized by cooperation. Webster’s dictionary [118] defines “cooperate” as “to associate with anoth er or others for mutual, often economic, benefit”. Explicit definitions of cooperation in the robotics literature, while surprisingly sparse, include:1. “joint collaborative behavior that is directed toward some goal in which there is a common interest or reward” [22];2. “a form of interaction, usually based on communication” [108]; and3. “[joining] together for doing something that creates a progressive result such as increasing performance or saving time” [137].These definitions show the wide range of possible motivating perspectives. For example, definitions such as (1) typically lead to the study of task decomposition, task allocation, and other dis-tributed artificial intelligence (DAI) issues (e.g., learning, rationality). Definitions along the lines of (2) reflect a concern with requirements for information or other resources, and may be accompanied by studies of related issues such as correctness and fault-tolerance. Finally, definition (3) reflects a concern with quantified measures of cooperation, such as speedup in time to complete a task. Thus, in these definitions we see three fundamental seeds: the task, the mechanism of cooperation, and system performance.We define cooperative behavior as follows: Given some task specified by a designer, a multiple-robot system displays cooperative behavior if, due to some underlying mechanism (i.e., the “mechanism of cooperation”), there is an increase in the total utility of the system. Intuitively, cooperative behavior entails some type of performance gain over naive collective behavior. The mechanism of cooperation may lie in the imposition by the designer of a control or communication structure, in aspects of the task specification, in the interaction dynamics of agent behaviors, etc.In this paper, we survey the intellectual heritage and major research directions of the field of cooperative robotics. For this survey of cooperative robotics to remain tractable, we restrict our discussion to works involving mobile robots or simulations of mobile robots, where a mobile robot is taken to be an autonomous, physically independent, mobile robot. In particular, we concentrated on fundamental theoretical issues that impinge on cooperative robotics. Thus, the following related subjects were outside the scope of this work:•coordination of multiple manipulators, articulated arms, or multi-fingered hands, etc.•human-robot cooperative systems, and user-interface issues that arise with multiple-robot systems [184] [8] [124] [1].•the competitive subclass of coll ective behavior, which includes pursuit-evasion [139], [120] and one-on-one competitive games [12]. Note that a cooperative team strategy for, e.g., work on the robot soccer league recently started in Japan[87] would lie within our present scope.•emerging technologies such as nanotechnology [48] and Micro Electro-Mechanical Systems[117] that are likely to be very important to co-operative robotics are beyond the scope of this paper.Even with these restrictions, we find that over the past 8 years (1987-1995) alone, well over 200papers have been published in this field of cooperative (mobile) robotics, encompassing theories from such diverse disciplines as artificial intelligence, game theory/economics, theoretical biology, distributed computing/control, animal ethology and artificial life.We are aware of two previous works that have surveyed or taxonomized the literature. [13] is abroad, relatively succinct survey whose scope encompasses distributed autonomous robotic systems(i.e., not restricted to mobile robots). [50] focuses on several well-known “swarm” architectures (e.g., SWARM and Mataric’s Behavior-based architecture –see Section 2.1) and proposes a taxonomy to characterize these architectures. The scope and intent of our work differs significantly from these, in that (1) we extensively survey the field of co-operative mobile robotics, and (2) we provide a taxonomical organization of the literature based on problems and solutions that have arisen in the field (as opposed to a selected group of architectures). In addition, we survey much new material that has appeared since these earlier works were published.Towards a Picture of Cooperative RoboticsIn the mid-1940’s Grey Walter, along with Wiener and Shannon, studied turtle-like robots equipped wit h light and touch sensors; these simple robots exhibited “complex social behavior” in responding to each other’s movements [46]. Coordination and interactions of multiple intelligent agents have been actively studied in the field of distributed artificial intelligence (DAI) since the early 1970’s[28], but the DAI field concerned itself mainly with problems involving software agents. In the late 1980’s, the robotics research community be-came very active in cooperative robotics, beginning with projects such as CEBOT [59], SWARM[25], ACTRESS [16], GOFER [35], and the work at Brussels [151]. These early projects were done primarily in simulation, and, while the early work on CEBOT, ACTRESS and GOFER have all had physical implementations (with≤3 robots), in some sense these implementations were presented by way of proving the simulation results. Thus, several more recent works (cf. [91], [111], [131])are significant for establishing an emphasis on the actual physical implementation of cooperative robotic systems. Many of the recent cooperative robotic systems, in contrast to the earlier works, are based on a behavior-based approach (cf. [30]).Various perspectives on autonomy and on the connection between intelligence and environment are strongly associated with the behavior-based approach [31], but are not intrinsic to multiple-robot systems and thus lie beyond our present scope. Also note that a recent incarnation of CEBOT, which has been implemented on physical robots, is based on a behavior-based control architecture[34].The rapid progress of cooperative robotics since the late 1980’s has been an interplay of systems, theories and problems: to solve a given problem, systems are envisioned, simulated and built; theories of cooperation are brought from other fields; and new problems are identified (prompting further systems and theories). Since so much of this progress is recent, it is not easy to discern deep intellectual heritages from within the field. More apparent are the intellectualheritages from other fields, as well as the canonical task domains which have driven research. Three examples of the latter are:•Traffic Control. When multiple agents move within a common environment, they typically attempt to avoid collisions. Fundamentally, this may be viewed as a problem of resource conflict, which may be resolved by introducing, e.g., traffic rules, priorities, or communication architectures. From another perspective, path planning must be performed taking into con-sideration other robots and the global environment; this multiple-robot path planning is an intrinsically geometric problem in configuration space-time. Note that prioritization and communication protocols – as well as the internal modeling of other robots – all reflect possible variants of the group architecture of the robots. For example, traffic rules are commonly used to reduce planning cost for avoiding collision and deadlock in a real-world environment, such as a network of roads. (Interestingly, behavior-based approaches identify collision avoidance as one of the most basic behaviors [30], and achieving a collision-avoidance behavior is the natural solution to collision avoidance among multiple robots. However, in reported experiments that use the behavior-based approach, robots are never restricted to road networks.) •Box-Pushing/Cooperative Manipulation. Many works have addressed the box-pushing (or couch-pushing) problem, for widely varying reasons. The focus in [134] is on task allocation, fault-tolerance and (reinforcement) learning. By contrast, [45] studies two boxpushing protocols in terms of their intrinsic communication and hardware requirements, via the concept of information invariants. Cooperative manipulation of large objects is particularly interesting in that cooperation can be achieved without the robots even knowing of each others’ existence [147], [159]. Other works in the class of box-pushing/object manipulation include [175] [153] [82] [33] [91] [94] [92][114] [145] [72] [146].•Foraging. In foraging, a group of robots must pick up objects scattered in the environment; this is evocative of toxic waste cleanup, harvesting, search and rescue, etc. The foraging task is one of the canonical testbeds for cooperative robotics [32] [151] [10] [67] [102] [49] [108] [9][24]. The task is interesting because (1) it can be performed by each robot independently (i.e., the issue is whether multiple robots achieve a performance gain), and (2) as discussed in Section 3.2, the task is also interesting due to motivations related to the biological inspirations behind cooperative robot systems. There are some conceptual overlaps with the related task of materials handling in a manufacturing work-cell [47]. A wide variety of techniques have been applied, ranging from simple stigmergy (essentially random movements that result in the fortuitous collection of objects [24] to more complex algorithms in which robots form chains along which objects are passed to the goal [49].[24] defines stigmergy as “the production of a certain behaviour in agents as a consequence of the effects produced in the local environment by previous behaviour”. This is actually a form of “cooperation without communication”, which has been the stated object of several for-aging solutions since the corresponding formulations become nearly trivial if communication is used. On the other hand, that stigmergy may not satisfy our definition of cooperation given above, since there is no performance improvement over the “naive algorithm” –in this particular case, the proposed stigmergic algorithm is the naive algorithm. Again, group architecture and learning are major research themes in addressing this problem.Other interesting task domains that have received attention in the literature includemulti-robot security systems [53], landmine detection and clearance [54], robotic structural support systems (i.e., keeping structures stable in case of, say ,an earthquake) [107], map making [149], and assembly of objects using multiple robots [175].Organization of PaperWith respect to our above definition of cooperative behavior, we find that the great majority of the cooperative robotics literature centers on the mechanism of cooperation (i.e., few works study a task without also claiming some novel approach to achieving cooperation). Thus, our study has led to the synthesis of five “Research Axes” which we believe comprise the major themes of investigation to date into the underlying mechanism of cooperation.Section 2 of this paper describes these axes, which are: 2.1 Group Architecture, 2.2 Resource Conflict, 2.3 Origin of Cooperation, 2.4 Learning, and 2.5 Geometric Problems. In Section 3,we present more synthetic reviews of cooperative robotics: Section 3.1 discusses constraints arising from technological limitations; and Section 3.2discusses possible lacunae in existing work (e.g., formalisms for measuring performance of a cooperative robot system), then reviews three fields which we believe must strongly influence future work. We conclude in Section 4 with a list of key research challenges facing the field.2. Research AxesSeeking a mechanism of cooperation may be rephrased as the “cooperative behavior design problem”: Given a group of robots, an environment, and a task, how should cooperative behavior arise? In some sense, every work in cooperative robotics has addressed facets of this problem, and the major research axes of the field follow from elements of this problem. (Note that certain basic robot interactions are not task-performing interactions per se, but are rather basic primitives upon which task-performing interactions can be built, e.g., following ([39], [45] and many others) or flocking [140], [108]. It might be argued that these interactions entail “control and coordination” tasks rather than “cooperation” tasks, but o ur treatment does not make such a distinction).First, the realization of cooperative behavior must rely on some infrastructure, the group architecture. This encompasses such concepts as robot heterogeneity/homogeneity, the ability of a given robot to recognize and model other robots, and communication structure. Second, for multiple robots to inhabit a shared environment, manipulate objects in the environment, and possibly communicate with each other, a mechanism is needed to resolve resource conflicts. The third research axis, origins of cooperation, refers to how cooperative behavior is actually motivated and achieved. Here, we do not discuss instances where cooperation has been “explicitly engineered” into the robots’ behavior since this is the default approach. Instead, we are more interested in biological parallels (e.g., to social insect behavior), game-theoretic justifications for cooperation, and concepts of emergence. Because adaptability and flexibility are essential traits in a task-solving group of robots, we view learning as a fourth key to achieving cooperative behavior. One important mechanism in generating cooperation, namely,task decomposition and allocation, is not considered a research axis since (i) very few works in cooperative robotics have centered on task decomposition and allocation (with the notable exceptions of [126], [106], [134]), (ii) cooperative robot tasks (foraging, box-pushing) in the literature are simple enough that decomposition and allocation are not required in the solution, and (iii) the use of decomposition and allocation depends almost entirely on the group architectures(e.g. whether it is centralized or decentralized).Note that there is also a related, geometric problem of optimizing the allocation of tasks spatially. This has been recently studied in the context of the division of the search of a work area by multiple robots [97]. Whereas the first four axes are related to the generation of cooperative behavior, our fifth and final axis –geometric problems–covers research issues that are tied to the embed-ding of robot tasks in a two- or three-dimensional world. These issues include multi-agent path planning, moving to formation, and pattern generation.2.1. Group ArchitectureThe architecture of a computing sys tem has been defined as “the part of the system that remains unchanged unless an external agent changes it”[165]. The group architecture of a cooperative robotic system provides the infrastructure upon which collective behaviors are implemented, and determines the capabilities and limitations of the system. We now briefly discuss some of the key architectural features of a group architecture for mobile robots: centralization/decentralization, differentiation, communications, and the ability to model other agents. We then describe several representative systems that have addressed these specific problems.Centralization/Decentralization The most fundamental decision that is made when defining a group architecture is whether the system is centralized or decentralized, and if it is decentralized, whether the system is hierarchical or distributed. Centralized architectures are characterized by a single control agent. Decentralized architectures lack such an agent. There are two types of decentralized architectures: distributed architectures in which all agents are equal with respect to control, and hierarchical architectures which are locally centralized. Currently, the dominant paradigm is the decentralized approach.The behavior of decentralized systems is of-ten described using such terms as “emergence” and “self-organization.” It is widely claimed that decentralized architectures (e.g., [24], [10], [152],[108]) have several inherent advantages over centralized architectures, including fault tolerance, natural exploitation of parallelism, reliability, and scalability. However, we are not aware of any published empirical or theoretical comparison that supports these claims directly. Such a comparison would be interesting, particularly in scenarios where the team of robots is relatively small(e.g., two robots pushing a box), and it is not clear whether the scaling properties of decentralization offset the coordinative advantage of centralized systems.In practice, many systems do not conform toa strict centralized/decentralized dichotomy, e.g., many largely decentralized architectures utilize “leader” agents. We are not aware of any in-stances of systems that are completely centralized, although there are some hybrid centralized/decentralized architectures wherein there is a central planner that exerts high-levelcontrol over mostly autonomous agents [126], [106], [3], [36].Differentiation We define a group of robots to be homogeneous if the capabilities of the individual robots are identical, and heterogeneous otherwise. In general, heterogeneity introduces complexity since task allocation becomes more difficult, and agents have a greater need to model other individuals in the group. [134] has introduced the concept of task coverage, which measures the ability of a given team member to achieve a given task. This parameter is an index of the demand for cooperation: when task coverage is high, tasks can be accomplished without much cooperation, but otherwise, cooperation is necessary. Task coverage is maximal in homogeneous groups, and decreases as groups become more heterogeneous (i.e., in the limit only one agent in the group can perform any given task).The literature is currently dominated by works that assume homogeneous groups of robots. How-ever, some notable architectures can handle het-erogeneity, e.g., ACTRESS and ALLIANCE (see Section 2.1 below). In heterogeneous groups, task allocation may be determined by individual capabilities, but in homogeneous systems, agents may need to differentiate into distinct roles that are either known at design-time, or arise dynamically at run-time.Communication Structures The communication structure of a group determines the possible modes of inter-agent interaction. We characterize three major types of interactions that can be sup-ported. ([50] proposes a more detailed taxonomy of communication structures). Interaction via environmentThe simplest, most limited type of interaction occurs when the environment itself is the communication medium (in effect, a shared memory),and there is no explicit communication or interaction between agents. This modality has also been called “cooperation without communication” by some researchers. Systems that depend on this form of interaction include [67], [24], [10], [151],[159], [160], [147].Interaction via sensing Corresponding to arms-length relationships inorganization theory [75], interaction via sensing refers to local interactions that occur between agents as a result of agents sensing one another, but without explicit communication. This type of interaction requires the ability of agents to distinguish between other agents in the group and other objects in the environment, which is called “kin recognition” in some literatures [108]. Interaction via sensing is indispensable for modeling of other agents (see Section 2.1.4 below). Because of hard-ware limitations, interaction via sensing has often been emulated using radio or infrared communications. However, several recent works attempt to implement true interaction via sensing, based on vision [95], [96], [154]. Collective behaviors that can use this kind of interaction include flocking and pattern formation (keeping in formation with nearest neighbors).Interaction via communicationsThe third form of interaction involves explicit communication with other agents, by either directed or broadcast intentional messages (i.e. the recipient(s) of the message may be either known or unknown). Because architectures that enable this form of communication are similar tocommunication networks, many standard issues from the field of networks arise, including the design of network topologies and communications protocols. For ex-ample, in [168] a media access protocol (similar to that of Ethernet) is used for inter-robot communication. In [78], robots with limited communication range communicate to each other using the “hello-call” protocol, by which they establish “chains” in order to extend their effective communication ranges. [61] describes methods for communicating to many (“zillions”) robots, including a variety of schemes ranging from broadcast channels (where a message is sent to all other robots in the system) to modulated retroreflection (where a master sends out a laser signal to slaves and interprets the response by the nature of the re-flection). [174] describes and simulates a wireless SMA/CD ( Carrier Sense Multiple Access with Collision Detection ) protocol for the distributed robotic systems.There are also communication mechanisms designed specially for multiple-robot systems. For example, [171] proposes the “sign-board” as a communication mechanism for distributed robotic systems. [7] gives a communication protocol modeled after diffusion, wherein local communication similar to chemical communication mechanisms in animals is used. The communication is engineered to decay away at a preset rate. Similar communications mechanisms are studied in [102], [49], [67].Additional work on communication can be found in [185], which analyzes optimal group sizes for local communications and communication delays. In a related vein, [186], [187] analyzes optimal local communication ranges in broadcast communication.Modeling of Other Agents Modeling the intentions, beliefs, actions, capabilities, and states of other agents can lead to more effective cooperation between robots. Communications requirements can also be lowered if each agent has the capability to model other agents. Note that the modeling of other agents entails more than implicit communication via the environment or perception: modeling requires that the modeler has some representation of another agent, and that this representation can be used to make inferences about the actions of the other agent.In cooperative robotics, agent modeling has been explored most extensively in the context of manipulating a large object. Many solutions have exploited the fact that the object can serve as a common medium by which the agents can model each other.The second of two box-pushing protocols in[45] can achieve “cooperation without commun ication” since the object being manipulated also functions as a “communication channel” that is shared by the robot agents; other works capitalize on the same concept to derive distributed control laws which rely only on local measures of force, torque, orientation, or distance, i.e., no explicit communication is necessary (cf. [153] [73]).In a two-robot bar carrying task, Fukuda and Sekiyama’s agents [60] each uses a probabilistic model of the other agent. When a risk threshold is exceeded, an agent communicates with its partner to maintain coordination. In [43], [44], the theory of information invariants is used to show that extra hardware capabilities can be added in order to infer the actions of the other agent, thus reducing communication requirements. This is in contrast to [147], where the robots achieve box pushing but are not aware of each other at all. For a more com-plex task involving the placement of five desks in[154], a homogeneous group of four robots share a ceiling camera to get positional information, but do not communicate with each other. Each robot relies on modeling of otheragents to detect conflicts of paths and placements of desks, and to change plans accordingly.Representative Architectures All systems implement some group architecture. We now de-scribe several particularly well-defined representative architectures, along with works done within each of their frameworks. It is interesting to note that these architectures encompass the entire spectrum from traditional AI to highly decentralized approaches.CEBOTCEBOT (Cellular roBOTics System) is a decentralized, hierarchical architecture inspired by the cellular organization of biological entities (cf.[59] [57], [162] [161] [56]). The system is dynamically reconfigurable in tha t basic autonomous “cells” (robots), which can be physically coupled to other cells, dynamically reconfigure their structure to an “optimal” configuration in response to changing environments. In the CEBOT hierarchy there are “master cells” that coordinate subtasks and communicate with other master cells. A solution to the problem of electing these master cells was discussed in [164]. Formation of structured cellular modules from a population of initially separated cells was studied in [162]. Communications requirements have been studied extensively with respect to the CEBOT architecture, and various methods have been proposed that seek to reduce communication requirements by making individual cells more intelligent (e.g., enabling them to model the behavior of other cells). [60] studies the problem of modeling the behavior of other cells, while [85], [86] present a control method that calculates the goal of a cell based on its previous goal and on its master’s goal. [58] gives a means of estimating the amount of information exchanged be-tween cells, and [163] gives a heuristic for finding master cells for a binary communication tree. Anew behavior selection mechanism is introduced in [34], based on two matrices, the priority matrix and the interest relation matrix, with a learning algorithm used to adjust the priority matrix. Recently, a Micro Autonomous Robotic System(MARS) has been built consisting of robots of 20cubic mm and equipped with infrared communications [121].ACTRESSThe ACTRESS (ACTor-based Robot and Equipments Synthetic System) project [16], [80],[15] is inspired by the Universal Modular AC-TOR Formalism [76]. In the ACTRESS system,“robotors”, including 3 robots and 3 workstations(one as interface to human operator, one as im-age processor and one as global environment man-ager), form a heterogeneous group trying to per-form tasks such as object pushing [14] that cannot be accomplished by any of the individual robotors alone [79], [156]. Communication protocols at different abstraction levels [115] provide a means upon which “group cast” and negotiation mechanisms based on Contract Net [150] and multistage negotiation protocols are built [18]. Various is-sues are studied, such as efficient communications between robots and environment managers [17],collision avoidance [19].SWARM。

本科毕业设计（论文）中英文对照翻译(此文档为word格式,下载后您可任意修改编辑!)原文The investigation of an autonomous intelligent mobile robot systemfor indoor environment navigationS KarelinAbstractThe autonomous mobile robotics system designed and implemented for indoor environment navigation is a nonholonomic differential drive system with two driving wheels mounted on the same axis driven by two PID controlled motors and two caster wheels mounted in the front andback respectively. It is furnished with multiple kinds of sensors such as IR detectors ,ultrasonic sensors ,laser line generators and cameras,constituting a perceiving system for exploring its surroundings. Its computation source is a simultaneously running system composed of multiprocessor with multitask and multiprocessing programming. Hybrid control architecture is employed on the rmbile robot to perform complex tasks. The mobile robot system is implemented at the Center for Intelligent Design , Automation and Manufacturfing of City University of Hong Kong.Key words:mobile robot ; intelligent control ; sensors ; navigation IntroductionWith increasing interest in application of autonomous mobile robots in the factory and in service environments，many investigations have been done in areas such as design，sensing，control and navigation，etc. Autonomousreaction to the real wand，exploring the environment，follownng the planned path wnthout collisions and carrying out desired tasks are the main requirements of intelligent mobile robots. As humans，we can conduct these actions easily. For robots however，it is tremendously difficult. An autonomous mobile robot should make use of various sensors to sense the environment and interpret and organize the sensed information to plan a safe motion path using some appropriate algorithms while executing its tasks. Many different kinds of senors havebeen utilized on mobile robots，such as range sensors，light sensors，force sensors，sound sensors，shaft encoders，gyro scope s，for obstacle awidance，localizatio n，rmtion sensing，navigation and internal rmnitoring respectively. Many people use infrared and ultrasonic range sensors to detect obstacles in its reaching ser range finders are also employed in obstacle awidance behavior of mobile robots in cluttered space.Cameras are often introduced into the vision system for mobile robot navigation. Although many kinds of sensors are available，sensing doesn’t mean perceiving. The mechanical shape and driving type are commonly first taken into consideration while implementing a rmbile robot. A robot’s shape can have a strong impact on how robust it is，and DC serve rmtors or stepOper motors are often the two choices to employ as actuators. The shape of a robot may affect its configurations of components，ae sthetics，and even the movement behaviors of the robot. An improper shape can make robot run a greater risk of being trapped in a cluttered room or of failing to find its way through a narrow space. We choose an octahedral shape that has both advantages of rectangular and circular shapes，and overcomes their drawbacks. The framework of the octahedral shaped robot is easy to make，components inside are easily arrange and can pass through narrow places and rotate wrath corners and nearby objects，and is more aesthetic in appearance. The perception subsystem accomplishes the task of getting various data from thesurroundings，including distance of the robot from obstacles，landmarks，etc.Infrared and ultrasonic range sen}rs，laser rangefinders and cameras are utilized and mounted on the rmbile robot to achieve perception of the environment. These sensors are controlled independently by some synchronously running microprocessors that are arranged wrath distributive manner，and activated by the main processor on which a supervising program runs. At present，infrared and ultranic sensors，laser rangefinders are programmed to detect obstacles and measure distance of the robot from objects in the environment，and cameras are programmed for the purpose of localization and navigation.The decision-making subsystem is the most important part of an intelligent mobile robot that organizes and utilizes the information obtained from the perception subsystem. It obtains reasonable results by some intelligent control algorithm and guides the rmbile robot. On our mobile robotic system intelligence is realized based on behaviourism and classical planning principles. The decision-making system is composed of twa levels global task planning based on knowledge base and map of working enviro nment，reactive control to deal with the dynamic real world. Reaction tasks in the decision-making system are decomposed into classes of behaviors that the robot exhibits to accomplish the task. Fuzzy logic is used to implement some basic behaviors. A state machine mechanism is applied to coordinate different behaviors. Because manykinds of electronic components such as range sensors，cameras，frame grabbers，laser line generators，microprocessors，DC motors，encoders，are employed on the mobile robot，a power source must supply various voltage levels which should are stable and have sufficient power. As the most common solution to power source of mobile robots，two sealed lead acid batteries in series writh 24 V output are employed in our mobile robot for the rmtor drive components and electronic components which require 24 V，15V，士12V，+9V，士5V，variously. For the conversion and regulation of the voltage，swritching DC DC converters are used because of their high efficiency，low output ripple and noise，and wride input voltage range. Three main processors are Motorola MC68040 based single board computers on which some supervisory programs and decision-making programs run. These MC68040 boards run in parallel and share memory using a VMEbus. Three motorola MC68HC11 based controllers act as the lower level controllers of the infrared and ultranic range senors，which communicate with the main processors through serial ports. The multi-processor system is organized into a hierarchical and distributive structure to implement fast gathering of information and rapid reaction. Harmony，a multiprocessing and multitasking operating system for real-time control，runs on the main processors to implement multiprocessing and multitasking programming. Harmony is a runtime only environment and program executions are performed by downloadingcrosscompiled executable images into target processors. The hardware architecture of the mobile robot is shown in Fig. Robots control For robots，the three rmst comrmn drive systems are wheels，tracks and legs. Wheeled robots are mechanically simpler and easier to construct than legged and tracked systems that generally require more complex and heavier hardware，so our mobile robot is designed as a wheeled robot. For a wheeled robot，appropriate arrangements of driving and steering wheels should be chosen from differential，synchro，tricycle，and automotive type drive mechanisms. Differential drives use twa caster wheels and two driven wheels on a common axis driven independently，which enable the robot to move straight，in an arc and turn in place. All wheels are rotate simultaneously in the synchro drive;tricycle drive includes two driven wheels and one steering wheel;automobile type drive rotates the front twa wheels together like a car. It is obvious that differential drive is the simplest locomotion system for both programming and construction.However，a difficult problem for differentially driven robots is how to make the robot go straight，especially when the motors of the two wheels encounter different loads. To follow a desired path，the rmtor velocity must be controlled dynamically. In our mobile robot system a semv motor controller is used which implements PID control.Ibwer amplifiers that drive the motors amplify the signals from each channel of serwcontroller. Feedback is provided by shaft encoders on the wheels.The block diagram of the motor control electronic components are shown in Fig. 2，and the strategy of two wheel speed control based PID principle is illustrated in Fig.3. Top loop is for tracking the desired left motor velocity;bottom loop for tracking right motor velocity;Integral loop ensures the robot to go straight as desired and controls the steering of the robot. This is a simple PI control that can satisfy the general requirements.Sensing subsystemSensor based planning makes use of sensor information reflecting the current state of the environment，in contrast to classical planning，which assumes full knowledge of the environment prior to planning. The perceptive subsystem integrates the visual and proximity senors for the reaction of the robot. It plays an important role in the robot behavioral decision-making processes and motion control. Field of view of perceptive subsystem is the first consideration in the design of the sensing system. Fneld of view should be wide enough with sufficient depth of field to understand well the robot’s surroundings. Multiple sensors can provide information that is difficult to extract from single sensor systems. Multiple sensors are complementary to each other，providing a better understanding of the work environment. Omnidirectional sensory capability is endowed on our mobile robot. When attempting to utilize multiple senors，it must be decided how many different kinds of sensorsare to be used in order to achieve the desired motion task，both accurately and economically.Ultrasonic range sensing is an attractive sensing rmdalityfor mobile robots because it is relatively simple to implement and process，has low cost and energy consumption. In addition，high frequencies can be used to minimize interference from the surrounding environment. A special purpose built infrared ranging system operates similar to sonar，determining the obstacle’s presence or absence and also the distance to an object. For detecting smaller obstacles a laser rangefinder can be used. It can be titled down to the ground to detect the small objects near the robot. Identifying robot self position and orientation is a basic behavior that can be part of high level complex behaviors. For localizing a dead reckoning method is adopted using the output of shaft encoders. This method can have accumulated error on the position and orientation. Many external sensors can be used for identification of position and orientation. Cameras are the most popular sensor for this purpose，because of naturally occurring features of a mom as landmarks，such as air conditioning system，fluorescent lamps，and suspended ceiling frames.Any type of sensor has inherent disadvantages that need to be taken into consideration. For infrared range senors，if there is a sharply defined boundary on the target betweendifferent materials，colors，etc.，the sensor may not be able to calculate distance accurately. Some of these problemscan be avoided if due care is taken when installing and setting up the sensor. Crosstalk and specular reflection are the two main problems for ultrasonic sensors. The firing rates，blanking intervals，firing order，and timeouts of the ultrasonic sensor system can configured to improve performance. Laser ranging systems can fail to detect objects made of transparent materials or with poor light reflectivity. In this work，we have chosen range sensors and imaging sensors as the primary source of information. The range sensors employed include ultrasonic sensors and short and long range infrared sensors with features above mentioned. The imaging sensors comprise gray scale video cameras and laser rangefinders. Twenty-four ultrasonic sensors are arranged in a ring with a separation angle of 15 degrees on our mobile robot to detect the objects in a 3600 field of view. This will allow the robot to navigatearound an unstructured environment and to construct ac curate sonar maps by using environmental objects as naturally occurring beacons. With the sonar system we can detect objects from a minimum range of 15 cm to a maximum range of 10. 0 m. Infrared range sensors use triangulation，emitting an infrared spot from an emitter，and measuring the position of the imaged spot with a PSD (position sensitive detector).Since these devices use triangulation，object color，orientation，and ambient light have greater effect on sensitivity rather than accuracy. Since the transmission signal is light instead of sound，we may expect a dramatically shortercycle time for obtaining all infrared sensor measurements. A getup of 16 short and a group of 16 long infrared sensors are mounted in twa rings with equal angular Generally speaking，the robot motion closed control loops comprising sensing，planning，and acting should take very short cycle times，so a parallel computation mechanism is employed in our mobile robot based on multiprocessor. Usually we can make events run in parallel on single microprocessor or multiprocessor by twa methods，multitasking and multiprocessing. Well known multitasking OS is like Microsoft window' 95 and UNIX OS that can make multitask run in parallel on a sequential machine by giving a fraction of time to each behavior looply. In fact，multitask mechanism just simulates the effect of all events running simultaneously. Running all events on multiprocessor can realize true parallelism. In our mobile robot，using Harmony OS both multitasking and multiprocessing programming is implemented on multiprocessor (MC68040 processors) which share memories and communicate each other by VMEbus. Harmony allows creating many tasks as desired which can be map toseveral microprocesors and run in parallel .In addition，tasks written in C run on MC68040 can activate the assembly code in the MC68HC11 SBC which control infrared and ultrasonic sensors and get distances dates. These SBC run simultaneously with MC68040 processors. An instance of an implemented task structure is shown in Fng. 5.Some experiments，such as following lines，avoiding obstacles and area filling have been carried out on the rmbile system to demonstrates its real-time reactions to the working surroundings and robustness of the system. ConclusionWe have described the implementation of a intelligent mobile robot testbed for autonomous navigation in indoor environments and for investigation of relative theories and technologies of intelligent systems. The robot is furnished with range sensors，laser line generators and vision system to perceive its surroundings. Parallel computation based on multiprocessor is employed in the mobile robot to improve its power of reasoning and response. Low level processing and sensor control is carried out with low cost dedicated microcontrollers. A task based real-time operating system supports a variety of different control structures，allowing us to experiment with different approaches. The experiments indicate the effectiveness of the mobile robot system .The platform has been used for experimenu and research such as sensor data fusion，area filling，feedback control，as well as artificial intelligence.译文基于室内环境导航的智能自动移动机器人系统研究卡若琳摘要这种为室内境导航条件下设计生产的自主移动机器人系统是一个不完整的差速传动系统，它有两个安装在同一轴上通过两个PID控制的电机驱动的驱动轮和两个分别安装在前部和后部的脚轮。

外文翻译外文资料：RobotsFirst, I explain the background robots, robot technology development. It should be said it is a common scientific and technological development of a comprehensive results, for the socio-economic development of a significant impact on a science and technology. It attributed the development of all countries in the Second World War to strengthen the economic input on strengthening the country's economic development. But they also demand the development of the productive forces the inevitable result of human development itself is the inevitable result then with the development of humanity, people constantly discuss the natural process, in understanding and reconstructing the natural process, people need to be able to liberate a slave. So this is the slave people to be able to replace the complex and engaged in heavy manual labor, People do not realize right up to the world's understanding and transformation of this technology as well as people in the development process of an objective need. Robots are three stages of development, in other words, we are accustomed to regarding robots are divided into three categories. is a first-generation robots, also known as teach-type robot, it is through a computer, to control over one of a mechanical degrees of freedom Through teaching and information stored procedures, working hours to read out information, and then issued a directive so the robot can repeat according to the people at that time said the results show this kind of movement again, For example, the car spot welding robots, only to put this spot welding process, after teaching, and it is always a repeat of a work It has the external environment is no perception that the force manipulation of the size of the work piece there does not exist, welding 0S It does not know, then this fact from the first generation robot, it will exist this shortcoming, it in the 20th century, the late 1970s, people started to study the second-generation robot, called Robot with the feeling that This feeling with the robot is similar in function of a certain feeling, forinstance, force and touch, slipping, visual, hearing and who is analogous to that with all kinds of feelings, say in a robot grasping objects, In fact, it can be the size of feeling out, it can through visual, to be able to feel and identify its shape, size, color Grasping an egg, it adopted a acumen, aware of its power and the size of the slide. Third-generation robots, we were a robotics ideal pursued by the most advanced stage, called intelligent robots, So long as tell it what to do, not how to tell it to do, it will be able to complete the campaign, thinking and perception of this man-machine communication function and function Well, this current development or relative is in a smart part of the concept and meaning But the real significance of the integrity of this intelligent robot did not actually exist, but as we continued the development of science and technology, the concept of intelligent increasingly rich, it grows ever wider connotations.Now, I would like to briefly outline some of the industrial robot situation. So far, the industrial robot is the most mature and widely used category of a robot, now the world's total sales of 1.1 million Taiwan, which is the 1999 statistics, however, 1.1 million in Taiwan have been using the equipment is 75 million, this volume is not small. Overall, the Japanese industrial robots in this one, is the first of the robots to become the Kingdom, the United States have developed rapidly. Newly installed in several areas of Taiwan, which already exceeds Japan, China has only just begun to enter the stage of industrialization, has developed a variety of industrial robot prototype and small batch has been used in production.Spot welding robot is the auto production line, improve production efficiency and raise the quality of welding car, reduce the labor intensity of a robot. It is characterized by two pairs of robots for spot welding of steel plate, bearing a great need for the welding tongs, general in dozens of kilograms or more, then its speed in meters per second a 5-2 meter of such high-speed movement. So it is generally five to six degrees of freedom, load 30 to 120 kilograms, the great space, probably expected that the work of a spherical space, a high velocity, the concept of freedom, that is to say, Movement is relatively independent of the number of components, the equivalent of our body, waist is a rotary degree of freedom We have to be able to hold his arm, Arm can be bent, then this three degrees of freedom, Meanwhile there is a wristposture adjustment to the use of the three autonomy, the general robot has six degrees of freedom. We will be able to space the three locations, three postures, the robot fully achieved, and of course we have less than six degrees of freedom. Have more than six degrees of freedom robot, in different occasions the need to configure.The second category of service robots, with the development of industrialization, especially in the past decade, Robot development in the areas of application are continuously expanding, and now a very important characteristic, as we all know, Robot has gradually shifted from manufacturing to non-manufacturing and service industries, we are talking about the car manufacturer belonging to the manufacturing industry, However, the services sector including cleaning, refueling, rescue, rescue, relief, etc. These belong to the non-manufacturing industries and service industries, so here is compared with the industrial robot, it is a very important difference. It is primarily a mobile platform, it can move to sports, there are some arms operate, also installed some as a force sensor and visual sensors, ultrasonic ranging sensors, etc. It’s surrounding environment for the conduct of identification, to determine its campaign to complete some work, this is service robot’s one of the basic characteristics.For example, domestic robot is mainly embodied in the example of some of the carpets and flooring it to the regular cleaning and vacuuming. The robot it is very meaningful, it has sensors, it can furniture and people can identify, It automatically according to a law put to the ground under the road all cleaned up. This is also the home of some robot performance.The medical robots, nearly five years of relatively rapid development of new application areas. If people in the course of an operation, doctors surgery, is a fatigue, and the other manually operated accuracy is limited. Some universities in Germany, which, facing the spine, lumbar disc disease, the identification, can automatically use the robot-aided positioning, operation and surgery Like the United States have been more than 1,000 cases of human eyeball robot surgery, the robot, also including remote-controlled approach, the right of such gastrointestinal surgery, we see on the television inside. a manipulator, about the thickness fingers such a manipulator, inserted through the abdominal viscera, people on the screen operating the machines hand, it also used the method of laser lesion laser treatment, this is the case, peoplewould not have a very big damage to the human body.In reality, this right as a human liberation is a very good robots, medical robots it is very complex, while it is fully automated to complete all the work, there are difficulties, and generally are people to participate. This is America, the development of such a surgery Lin Bai an example, through the screen, through a remote control operator to control another manipulator, through the realization of the right abdominal surgery A few years ago our country the exhibition, the United States has been successful in achieving the right to the heart valve surgery and bypass surgery. This robot has in the area, caused a great sensation, but also, AESOP's surgical robot, In fact, it through some equipment to some of the lesions inspections, through a manipulator can be achieved on some parts of the operation Also including remotely operated manipulator, and many doctors are able to participate in the robot under surgery Robot doctor to include doctors with pliers, tweezers or a knife to replace the nurses, while lighting automatically to the doctor's movements linked, the doctor hands off, lighting went off, This is very good, a doctor's assistant.Robot is mankind's right-hand man; friendly coexistence can be a reliable friend. In future, we will see and there will be a robot space inside, as a mutual aide and friend. Robots will create the jobs issue. We believe that there would not be a "robot appointment of workers being laid off" situation, because people with the development of society, In fact the people from the heavy physical and dangerous environment liberated, so that people have a better position to work, to create a better spiritual wealth and cultural wealth.译文资料：机器人首先我介绍一下机器人产生的背景，机器人技术的发展，它应该说是一个科学技术发展共同的一个综合性的结果，同时，为社会经济发展产生了一个重大影响的一门科学技术，它的发展归功于在第二次世界大战中各国加强了经济的投入，就加强了本国的经济的发展。