MCB －工業(yè)的機械手論文外文文獻翻譯巴雷特機械手爪－可編程式可彎曲部分的搬運和組裝外文翻譯/中英文翻譯

附錄 A MCB Industrial Robot Feature Article The BarrettHand grasper programmable flexible part handling and assembly Abstract This paper details the design and operation of the BarrettHand BH8-250, an intelligent, highly flexible eight-axis gripper that reconfigures itself in real time to conform securely to a wide variety of part shapes without tool-change interruptions. The grasper brings enormous value to factory automation because it: reduces the required number and size of robotic work cells (which average US$90,000 each not including the high cost of footprint) while boosting factory throughput； consolidates the hodgepodge proliferation of customized gripper-jaw shapes onto a common programmable platform； and enables incremental process improvement and accommodates frequent new-product introductions, capabilities deployed instantly via software across international networks of factories. Introduction This paper introduces a new approach to material handling, part sorting, and component assembly called “grasping”, in which a single reconfigurable grasper with embedded intelligence replaces an entire bank of unique, fixed-shape grippers and tool changers. To appreciate the motivations that guided the design of Barretts grasper, we must explore what is wrong with robotics today, the enormous potential for robotics in the future, and the dead-end legacy of gripper solutions. For the benefits of a robotic solution to be realized, programmable flexibility is required along the entire length of the robot, from its base, all the way to the target work piece. A robot arm enables programmable flexibility from the base only up to the tool plate, a few centimeters short of the target work piece. But these last few centimeters of a robot must adapt to the complexities of securing a new object on each robot cycle, capabilities where embedded intelligence and software excel. Like the weakest link in a serial chain, an inflexible gripper limits the productivity of the entire robot work cell. Grippers have individually-customized, but fixed jaw shapes. The trial-and-error customization process is design intensive, generally drives cost and schedule, and is difficult to scope in advance. In general, each anticipated variation in shape, orientation, and robot approach angle requires another custom-but-fixed gripper, a place to store the additional gripper, and a mechanism to exchange grippers. An unanticipated variation or incremental improvement is simply not allowable. By contrast, the mechanical structure of Barretts patented grasper, illustrated in Figure 1, is automatically reconfigurable and highly programmable, matching the functionality of virtually any gripper shape or fixture function in less than a second without pausing the work cell throughput to exchange grippers. For tasks requiring a high degree of flexibility such as handling variably shaped payloads presented in multiple orientations, a grasper is more secure, quicker to install, and more cost effective than an entire bank of custom-machined grippers with tool changers and storage racks. For uninterrupted operation, just one or two spare graspers can serve as emergency backups for several work cells, whereas one or two spare grippers are required for each gripper variation potentially dozens per work cell. And, its catastrophic if both gripper backups fail in a gripper system, since it may be days before replacements can be identified, custom shaped from scratch, shipped, and physically replaced to bring the affected line back into operation. By contrast, since graspers are physically identical, they are always available in unlimited quantity, with all customization provided instantly in software. Gripper legacy Most of todays robotic part handling and assembling is done with grippers. If surface conditions allow, vacuum suction and electromagnets can also be used, for example in handling automobile windshields and body panels. As part sizes begin to exceed the order of 100gms, a grippers jaws are custom shaped to ensure a secure hold. As the durable mainstay of handling and assembly, these tools have changed little since the beginning of robotics three decades ago. Grippers, which act as simple pincers, have two or three unarticulated fingers, called “jaws”, which either pivot or remain parallel during open/close motions as illustrated in Figure 2. Well organized catalogs are available from manufacturers that guide the integrator or customer in matching various gripper components (except naturally for the custom jaw shape) to the task and part parameters. Payload sizes range from grams for tiny pneumatic grippers to 100+ kilograms for massive hydraulic grippers. The power source is typically pneumatic or hydraulic with simple on/off valve control switching between full-open and full-close states. The jaws typically move 1cm from full-open to full-close. These hands have two or three fingers, called “jaws”. The part of the jaw that contacts the target part is made of a removable and machine ably soft steel or aluminum, called a “soft jaw”. Based on the unique circumstances, an expert tool designer determines the custom shapes to be machined into the rectangular soft-jaw pieces. Once machined to shape, the soft-jaw sets are attached to their respective gripper bodies and tested. This process can take any number of iterations and adjustments until the system works properly. Tool designers repeat the entire process each time a new shape is introduced. As consumers demand a wider variety of product choices and ever more frequent product introductions, the need for flexible automation has never been greater. However, rather than make grippers more versatile, the robotics industry over the past few years has followed the example of the automatic tool exchange technique used to exchange CNC-mill cutting tools. But applying the tool-changer model to serial-link robots is proving expensive and ineffective. Unlike the standardized off-the-shelf cutting tools used by milling machines, a robot tool designer must customize the shape of every set of gripper jaws a time-consuming, expensive, and difficult-to-scope task. Although grippers may seem cheap at only US$500 each, the labor-intensive effort to shape the soft jaws may cost several times that. If you multiply that cost times a dozen grippers as in the example above and throw in a tool changer and tool-storage rack for an additional US$10,000, the real cost of the “few-hundred-dollar” gripper solution balloons to US$20,000 to US$60,000. To aggravate matters, unknowns in the customization process confound accurate cost projections. So the customer must commit a purchase order to the initial installation fee on a time and materials basis without guarantee of success or a cost ceiling. While priced at US$30,000, intelligent graspers are not cheap. However, one can “customize” and validate the process in software in a matter of hours at the factory in a single day. If the system does not meet performance targets, then only a days labor is wasted. If the system succeeds, then there are not any hidden expenses following the original purchase order. Beyond cost, the physical weight of tool changer mechanisms, located at the extreme outer end of a serial-link robotic arm, limits the useful payload and dynamic response of the entire system. The additional length of the tool changer increases the critical distance between the wrist center and payload center, degrading kinematic flexibility, dynamic response, and safety. Description of the BarrettHand Flexibility and durability in a compact package The flexibility of the BarrettHand is based on the articulation of the eight joint axes identified in Figure 3. Only four brushless DC servomotors, shown in Figure 4, are needed to control all eight joints, augmented by intelligent mechanical coupling. The resulting 1.18kg grasper is completely self-contained with only an 8mm diameter umbilical cable supplying DC power and establishing a two-way serial communication link to the main robot controller of the work cell. The graspers communications electronics, five microprocessors, sensors, signal processing electronics, electronic commutation, current amplifiers, and brushless servomotors are all packed neatly inside the palm body of the grasper. The BarrettHand has three articulated fingers and a palm as illustrated in Figure 5 which act in concert to trap the target object firmly and securely within a grasp consisting of seven coordinated contact vectors one from the palm plate and one from each link of each finger. Each of the BarrettHands three fingers is independently controlled by one of three servomotors as shown in Figure 6. Except for the spread action of fingers Fl and F2, which is driven by the fourth and last servomotor, the three fingers, Fl, F2, and F3, have inner and outer articulated links with identical mechanical structure. Each of the three finger motors must drive two joint axes. The torque is channeled to these joints through a patented, TorqueSwitch mechanism (Figure 7), whose function is optimized for maximum grasp security. When a fingertip, not the inner link, makes first contact with an object as illustrated in Figure 8, it simply reaches its required torque, locks both joints, switches off motor currents, and awaits further instructions from the microprocessors inside the hand or a command arriving across the communications link. But when the inner link, as illustrated in Figure 9, makes first contact with an object for a secure grasp, the TorqueSwitch, reaches a preset threshold torque, locks that joint against the object with a shallow-pitch worm, and redirects all torque to the fingertip to make a second, enclosing contact against the object within milliseconds of the first contact. The sequence of contacts is so rapid that you cannot visualize the process without the aid of high-speed photography. After the grasper releases the object, it sets the TorqueSwitch threshold torque for each finger in anticipation of the next grasp by opening each finger against its mechanical stop with a controlled torque. The higher the opening torque, the higher the subsequent threshold torque. In this way, the grasper can accommodate a wide range of objects from delicate, to compliant, to heavy. The finger articulations, not available on conventional grippers, allow each digit to conform uniquely and securely to the shape of the object surface with two independent contact points per finger. The position, velocity, acceleration, and even torque can all be processor controlled over the full range of 17,500 encoder positions. At maximum velocity and acceleration settings, each finger can travel full range in either direction in less than one second. The maximum force that can be actively produced is 2kg, measured at the tip of each finger. Once the grasp is secure, the links automatically lock in place allowing the motor currents to be switched off to conserve power until commanded to readjust or release their grasp. While the inner and outer finger-link motions curl anthropomorphically, the spread motion of Figure 10 is distinctly non-anthropomorphic. The spread motion is closest in function to a primates opposable (thumb) finger, but instead of one opposable finger, the BarrettHand has twin, symmetrically opposable fingers centered on parallel joint axes rotating 180 degrees around the entire palm to form a limitless variety of gripper-shapes and fixture functions. The spread can be controlled to any of 3,000 positions over its full range in either direction within 1/2 second. Unlike the mechanically lockable finger-curl motions, the spread motion is fully back drivable, allowing its servos to provide active stiffness control in addition to control over position, velocity, acceleration, and torque. By allowing the spread motion to be compliant while the fingers close around an object, the grasper seeks maximum grasp stability as the spread accommodates its position, permitting the fingers to find their lowest energy states in the most concave surface features. Electronic and mechanical optimization Intelligent, dexterous control is key to the success of any programmable robot, whether it is an arm, automatically guided vehicle, or dexterous hand. While robotic intelligence is usually associated with processor-driven motor control, many biological systems, including human hands, integrate some degree of specialized reflex control independent of explicit motor-control signals from the brain. In fact, the BarrettHand combines reflexive mechanical intelligence and programmable microprocessor intelligence for a high degree of practical dexterity in real-world applications. By strict mathematical definition, dexterity requires independent, intelligent motor control over each and every articulated joint axis. For a robot to be dexterous, at least n independent servomotors, and sometimes as many as n + 1 or 2n, are required to drive n joint axes. Unfortunately, servomotors constitute the bulkiest, costliest, and most complex components of any dexterous robotic hand. So, while the strict definition of dexterity may be mathematically elegant, it leads to impractical designs for any real application. According to the definition, neither your hand nor the BarrettHand is dexterous. Naturally, their superior versatility challenges the definition itself. If the BarrettHand followed the strict definition for dexterity, it would require between eight and 16 motors, making it far too bulky, complex, and unreliable for any practical application outside the mathematical analysis of hand dexterity. But, by exploiting four intelligent, joint-coupling mechanisms, the almost-dexterous BarrettHand requires only four servomotors. In some instances reflex control is even better than deliberate control. Two examples based on your own body illustrate this point. Suppose your hand accidentally touches a dangerously hot surface. It begins retracting itself instantly, relying on local reflex to override any ongoing cognitive commands. Without this reflex behavior, your hand would burn while waiting for the sensations of pain to travel from your hand to your brain via relatively slow nerve fibers and then for your brain, through the same slow nerve fibers, to command your arm, wrist, and finger muscles to retract. As the second example, try to move the outer joint of your index finger without moving the adjacent joint on the same finger. If you are like most people, you cannot move these joints independently because the design of your hand is optimized for grasping. Your muscles and tendons are as streamlined and lightweight as possible without forfeiting functionality. The design of the BarrettHand recognizes that intelligent control of functional dexterity requires the integration of microprocessor and mechanical intelligence. Control electronics Inside its compact palm, the BarrettHand contains its central supervisory microprocessor that coordinates four dedicated motion-control microprocessors and controls I/O via the RS232 line. The control electronics, partially visible in Figure 4 are built on a parallel 70-pin backplane bus. Associated with each motion-control microprocessor are the related sensor electronics, motor commutation electronics, and motor-power current-amplifier electronics for that finger or spread action. The supervisory microprocessor directs I/O communication via a high-speed, industry-standard RS232 serial communications link to the work cell PC or controller. RS232 allows compatibility with any robot controller while limiting umbilical cable diameter for all power and communications to only 8mm. The openly published grasper communications language (GSL) optimizes communications speed, exploiting the difference between bandwidth and time-of-flight latency for the special case of graspers. It is important to recognize that graspers generally remain inactive during most of the work cell cycle, while the arm is performing its gross motions, and are only active for short bursts at the ends of an arms trajectories. While the robotic arm requires high control bandwidth during the entire cycle, the grasper has plenty of time to receive a large amount of setup information as it approaches its target. Then, with precision timing, the work cell controller releases a “trigger”command, such as the ASCII character “C” for close, which begins grasp execution within a couple milliseconds. Grasper control language (GCL) The grasper can communicate and accept commands from any robot-work cell controller, PC, Mac, UNIX box, or even a Palm pilot via standard ASCII RS232-C serial communication the common denominator of communications protocols. Though robust, RS232 has a reputation for slow bandwidth compared to USB or FireWire standards, but its simplicity leads to small latencies for short bursts of data. By streamlining the GCL, we have achieved time of flight to execute and acknowledge a command (from the work cell controller to the grasper and then back again to the work cell controller) of the order of milliseconds. The initial effort to develop a highly optimized grasper language based on such a standard protocol means that the GCL is upwardly compliant with any future industry-standard protocol. The grasper has two control modes: supervisory and real time. Supervisory is the normal mode used to control the grasper. It is made up of a simple command structure, designed for optimal performance and minimized learning curve. Supervisory mode has the following grammatical structure: Object (prefix) Verb (command) Subject (parameters) Qualifiers (values) The prefix refers to motors 1 through 4 with the ASCII values for 1, 2, 3, and 4 corresponding to the fingers Fl, F2, F3, and the spread motion. Any number of prefixes may be used in any order. If the prefix is omitted, then the grasper applies the command to all available axes. As an example, the ASCII character “C” represents the command which drives the associated motor (s) at its individual default (or user defined) velocity and acceleration profile(s) until the motor(s) stops for the default (or user defined) number of milliseconds. As each motor reaches this state its position is locked mechanically in place. 1C closes finger Fl. 2C closes finger F2. 12C closes fingers Fl and F2. C is equivalent to 1234C and closes all three fingers and the spread motion. We also have defined “S” (derived from “spread”) as a shortcut for “4” and “G” (from “grasp”) as a short cut for “123”, so that: GC is equivalent to 123C SC is equivalent to 4C There are similar commands for opening fingers, moving any combination of the four axes to an array of positions, incremental opening and closing by default or user-defined distances, reading and setting user-defined parameter values, and reading the (optional) strain gages on the three fingers. The latest version of the BH8-250 firmware has 21 commands and 28 parameter settings, giving it almost unlimited flexibility. The real time mode is reserved for advanced uses such as real time teleportation control and is frequently accessed through Barretts user-friendly GUI for PCs running Windows95/98/NT. In real time mode, the user specifies a tailored packet-structure in supervisory mode. Barretts PC software gives the user a histogram of 20 successive time-of-flight tests so that the user can refine the packet structure by quantitatively balancing information content with latency. The GUI accelerates the prototyping of tasks and includes a pictorial of the grasper with sliders for position and rate control. The GUI also has a novel “Generate C+ Code” button which enables anyone to save and later recall successful algorithms without any knowledge of C or C+ programming. But, with C+ programming familiarity, you can also edit the code as desired. Once real time mode is initiated, packets are exchanged in full duplex until an ASCII control character is issued to break out of real time mode and return to supervisory mode. The system has proven effective and robust in a variety of customer applications. Conclusion Although the BarrettHand BH8-250 was only introduced commercially in 1999, 30 units have been put into service around the globe at a price of US$30,000 each. The largest concentration of graspers is among automotive manufacturers and suppliers in Japan, including Honda, Yamaha Motorcycles, and NGK (ceramic substrates for catalytic converters). At this time, these manufacturers are only beginning to explore the capabilities of this versatile device, while some customers, such as Fanuc Robotics and the US and Japanese space programs have become repeat customers. Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 MCB 工業(yè)的機械手論文 巴雷特機械手爪可編 程式可彎曲部分的搬運和組裝 摘要 本文詳細介紹了巴雷特機械手爪 BH8 250 型的設計和運行，一個智能的，靈活的八軸夾具 , 一個可以隨時進行自我完善 ,改變或者中斷各種危險行為的工具。機械手爪帶來巨大的價值 -工廠自動化 ,因為它 :降低所需機器人工作單元的數(shù)量和尺寸 (平均每項 90,000 美元不包括高成本的占地面積 ),從而提高了工廠的生產能力 ,通過一個可編程平臺控制整合了各種各樣的機械手抓 ；漸漸的改進和推出新產品介紹，通過工廠里的軟件進行國際聯(lián)網(wǎng)。 介紹 本文介紹了一種新的方法來進行材料處理，零件分類和構件組裝 ，我們稱它為“抓”，即一個單一的嵌入式智能可重構機械手爪，取代了獨特的，固定形狀的夾子和整個換刀庫。指導的目的是為了感謝巴雷特機械手爪的設計，今天我們必須探討什么是錯誤的機器人技術，機器人在未來的巨大潛力，以及以前遺留下來的行不通的手爪的解決方案。 為了實現(xiàn)機器人的優(yōu)秀解決方案，可編程的靈活性，需要沿著整個機器人的設計史，從它的誕生，到現(xiàn)在。機器人手臂能夠從基礎的編程升級到靈活性的鈑金，讓機器人的外殼越來越薄。但即使要讓這些機器人的外殼變薄，也必須嵌入智能軟件 Excel，以確保每個機器人能正常運轉和適應新的 復雜的功能。就像在串行鏈中最薄弱環(huán)節(jié)，不靈活的爪子限制了整個工作單元機器人的生產力。 機械爪子已經進行了獨特的設計，但是固定顎板的形狀還沒有確定。在設計的過程中，一般難以預計硬盤成本和進度的范圍。一般來說，機器人的每個形狀、方向和接近角的預期的變化，需要其他自定義，但是爪子固定的位置，存放爪子的地方和更換爪子的器械，是不容許擅自改變和增加的。 相比之下，巴雷特的專利機械手爪如圖 1 所示，機械結構，自動重新配置和高度可編程性，不到一秒鐘匹配，地工作單元不停頓的數(shù)據(jù)交換量，交換手爪的幾乎任意形狀的變換功能。 對于 需要處理的可變等多種有效載荷的方向，提出了高度靈活性的任務，一個能讓機械手爪更安全，更快捷的安裝，以及比定做加工夾具更低的成本和大容量的存儲機架。 不間斷運行時，工作單元只有一個或兩個備用機械手爪可以作為應急備份，而一個或兩個備用的手抓，是要求每個手爪都能變化 - 可能每個工作單元需要幾十人。而且，悲劇的是如果兩個手爪都系統(tǒng)備份，如果失敗，因為它會存儲前幾天的可以識別的數(shù)據(jù)，很多自定義形狀，裝運和自身裝配，所以會影響后面的操作。與此相反，由于機械手爪是數(shù)據(jù)相同，他們總是可以通過特定的軟件及時提供無限量的數(shù)據(jù) 。 傳統(tǒng)夾具 今天的機器人，裝配零件的處理大部分是通過夾具。如果表面的條件允許，真空吸力和電磁鐵也可以應用，例如：處理汽車擋風玻璃和車身。作為部分尺寸開始超過 100gms，顎板的自定義形狀，以確保安全運行。由于處理和裝配耐用的主體，這些工具沒有什么變化，因為機器人是從三十年以前才開始的。 夾具，可以看做簡單的類似鉗子的動作，有兩個或三個非鉸鏈手指，被稱為“鉗口”，保持平行或者進行打開或者觀關上的運動，如 2 所示。良好的組織目錄可從制造商那里得到客戶所匹配（除了自定義形成的素具）的各種組成手爪所需要的部分任務和 部分參數(shù)。 大型液壓夾鉗的有效載荷的尺寸范圍從微克至 100+公斤。驅動是典型的氣動或液動 ,用簡單的開 /關閥控制切換全開或全閉狀態(tài)。鉗口通常移動 1cm就可以全開至全關。這兩只手，兩個或三個手指，被稱為“鉗口”。對鉗口部分的制造目標是可移動的機械軟鋼或鋁，被稱為“軟鉗口”。 在特殊的情況下，工具專家設計師決定要對矩形軟鉗口件進行自定義加工。一旦加工形狀完成，軟鉗口夾持器就要連接到各自的機構進行測試。這一過程可以采取任何數(shù)量的迭代和調整，直到系統(tǒng)正常工作。模具設計者需要時間來重復整個過程中每一個新的形態(tài)。 隨著消 費者需求產品選擇的多元化，更加頻繁的產品介紹，對可調節(jié)自動化的需求前所未有地強烈。然而，并沒有使機械手爪更全面，在過去幾年中機器人產業(yè)一直遵循的工具自動來交換數(shù)控磨刀具技術的例子。 但是，應用換模型串行工具連接機器人證明是昂貴的和無效的。不同于使用標準規(guī)范外的銑床工具進行成品切割，機器人工具設計者必須定制每一套機械爪的形狀 ， 一個耗時多、昂貴且難以確定范圍的任務。雖然機械手爪只便宜了 500 美元，但是每個工人努力制造機械手爪會耗資數(shù)倍。通過上面的例子，如果你要增加 12 個爪子的換刀架和刀具庫，那么花費就不止10,000 美元，而是劇增到 20,000 美元至 60,000 元。 更嚴重的是，在定制過程中準確的預測成本將是未知數(shù)。因此，客戶必須提交一份包括初裝費、所需時間和材料的成本在內的采購訂單，這是是交易的基礎。雖然在美國售價 30,000 美元，智能機械手爪并不便宜。然而，人們可以“定制”在某一天運行一個小時軟件來驗證的系統(tǒng)的性能。如果系統(tǒng)的性能不能達到目標要求，那么那一天的勞動是白費的。如果系統(tǒng)成功，那么按照原訂單將沒有任何隱藏的費用。 除了成本、轉換機制的物理重量，在末端串行連接的機械臂外，限制了有效載荷和整個系統(tǒng)的 動態(tài)響應。該轉換長度增加了額外的有效載荷中心，運動的靈活性，動態(tài)響應和關鍵的安全距離。 巴雷特機械手爪的說明 靈活性和耐久性的簡潔介紹 巴雷特機械手爪在靈活性的基礎上，按圖 3 中確定的八種聯(lián)合軸連接。只有四個直流伺服電動機，如圖 4 所示，需要控制所有八個關節(jié)，由智能機械耦合增強。由此產生的機械手爪是自身總共只有一點一八公斤重，只有 8mm直徑的連接電纜提供直流電源，建立雙向串行通訊連接到機器人的主要工作單元控制器中。該機械手爪的通訊電子，五微處理器，傳感器，信號處理電路，電子換相，電流放大器，和伺服電機都整齊的安 裝在機械手的體內。 巴雷特機械手爪的手掌有三個手指關節(jié)，如圖 5 所示，通過聯(lián)系手掌及每個手指，協(xié)調他們的動作，能讓他們在目標范圍內，牢牢的抓住物體。 每個巴雷特機械手爪的三根手指都是由三個獨立伺服電機控制，如圖 6所示。除了 F1 手指和 F2 手指的伸展動作 , 都是由伺服電動機驅動， F1、 F2、F3 三個手指的內外部的機械結構都是用一樣的鉸鏈連接的。 三個手爪的每個馬達都必須驅動兩個關節(jié)軸。通過專用通道來控制扭矩，扭矩控制器如圖 7 所示，這些關節(jié)的作用是能讓爪子在抓東西時更安全。如圖 8 所示，當手爪第一次接觸物體時，需要 傳遞簡單的扭矩，確定他們的接合處，關閉電機電流，并等待手抓內部的微處理器發(fā)出進一步的指示命令。 但是，當扭矩控制器如圖 9 所示時，為使安全和控制，扭矩控制機制第一次接觸物體時，用事先設置好的扭矩的上限值，再次確定物體螺紋的聯(lián)系，并當手爪第二次接觸時，在一毫秒之內更改第一次接觸時的所有扭矩信息。接觸順序快速確定，沒有高速攝像機的幫助下你將無法想象其中的過程。當機械手爪放開被抓對象時，它會讓扭矩控制器對每個手爪的扭矩的上限值進行設定，而可控扭矩可以讓機械的停止的爪子再一次打開。當扭矩達到最高，那就是它的上限。這樣 的話，機械手爪就有一個可抓起物體重量的準確范圍。 與傳統(tǒng)的機械手爪不同，這種手抓里的連接，容許每個手指的兩個一致的獨立接觸點來穩(wěn)固的抓住物體的表面。不管位置，速度，加速度，還是扭矩，都可以通過所有 17,500 種型號的編碼器進行控制處理。當速度和加速度設置為最大時，每個手指可以在不到一秒鐘的時間內向任何一個的方向上進行運動。通過測量，每個手指都能夠迅速的產生 2 公斤的力。一旦確定穩(wěn)定的抓住物體時，則鏈接將自動鎖定，并關掉電機，這樣可以節(jié)省電源，直到需要重新調整或者放開物體時，電機會自動打開。 雖然手抓的張開與收 縮是擬人化，但如圖 10 所示，清楚的顯示了機器的非擬人化。機器伸展的動作非常近似于靈長類動物的手指（拇指）的動作，但是又不能替代，巴雷特機械手爪還有一種類似的手爪，整個手爪可以旋轉180 度，手指中心對稱且平行于連接軸，是一種可以抓住各種夾具形狀的多功能手爪。 在 1/2 秒內可控制的機器在 3000位置中任意伸展。不同的是機械鎖定了手爪伸縮的運動，使伸縮運動變回了可驅動狀態(tài)，允許其控制手爪的位置，速度，加速度和扭矩。通過允許手爪的伸縮運動，使手指緊密的感應物體，機械手爪的主要目的是找到一個接觸面積最大的同時耗 能又是最小的地方。 電子和機械的優(yōu)化 可編程機器人智能靈巧的控制是成功的關鍵，不論是控制機械手臂，自動引導