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中原工學(xué)院畢業(yè)設(shè)計翻譯
靈巧機器手的機械系統(tǒng)和控制系統(tǒng)
文章來源：德克-亨氏卡爾斯魯厄大學(xué)計算機科學(xué)系研究所過程控制和機器人
技術(shù) 恩格勒-班泰環(huán)8 樓40.28 的D - 76131 卡爾斯魯厄
摘要：最近，全球內(nèi)帶有多指夾子或手的機械人系統(tǒng)已經(jīng)發(fā)展起來了，多種方法應(yīng)用其上，有擬人化和非擬人化的，不僅調(diào)查了這些系統(tǒng)的機械結(jié)構(gòu)，而且還包括其必要的控制系統(tǒng)，如同人手一樣，這些機械人系統(tǒng)可以用它們的手去抓不同的物體，而且不用改換夾子，這些機械手具備特殊的運動能力比如小質(zhì)量和小慣量，這使被抓物體在機械手的工作范圍內(nèi)做更復(fù)雜、更精確的操作變得可能。這些復(fù)雜的操作被抓物體繞任意角度和軸旋轉(zhuǎn)。本文概述了這種機械手的一般設(shè)計方法，同時給出此類機械手的一個示例，如卡爾斯魯靈巧手Ⅱ。本文末介紹了一些新的構(gòu)想，如利用液體驅(qū)動器為類人型機器人設(shè)計一個全新的機械手。
關(guān)鍵詞：多指機器手；機器人手；精操作；機械系統(tǒng)；控制系統(tǒng)
1、引言
2010 年7 月在德國卡爾斯魯厄開展的“人形機器人”特別研究，是為了開發(fā)在正常環(huán)境如廚房或客廳下能夠和人類合作和互動的機器人系統(tǒng)。設(shè)計這些機器人系統(tǒng)是為了能夠在非專業(yè)、非工業(yè)的條件下如身處多物之中，幫我們抓取不同大小、形狀和重量的物體。同時，它們必須能夠精細(xì)的操縱被抓物體。這種極強的靈活性只能通過一個適應(yīng)性極強的機械人手抓系統(tǒng)來獲得，即所謂的多指機械手或機器人。上文提到的研究項目，就是要制造一個人形機器人，此機器人將裝備這種機器人手系統(tǒng)。這個新手將有兩個機構(gòu)合作制造，它們是卡爾斯魯厄大學(xué)的IPR（過程控制和機器人技術(shù)研究院）和IAI 公司（計算機應(yīng)用科學(xué)研究院）。這兩個組織都有制造此種系統(tǒng)的相關(guān)經(jīng)驗，但是稍有不同的觀點。
圖1：IPR 制造的卡爾斯魯厄靈巧手Ⅱ
IPR 制造的卡爾斯魯厄靈巧手Ⅱ（如圖1 所示），是一個四指相互獨立的手爪，我們將在此文中詳細(xì)介紹。IAI 制造的手（如圖17 所示）是作為殘疾人的假肢。
2、 機器人手的一般結(jié)構(gòu)一個機器人手可分成兩大主要子系統(tǒng)：
·機械系統(tǒng)
·控制系統(tǒng)
機械系統(tǒng)我們將在第三部分作進一步介紹，能分別為以下三部分：
- 結(jié)構(gòu)設(shè)計
- 驅(qū)動系統(tǒng)
- 傳感系統(tǒng)
在第四部分介紹的控制系統(tǒng)至少包括：
- 控制硬件
- 控制軟件
我們將對這兩大子系統(tǒng)的問題作一番基本介紹，然后用卡爾斯魯厄靈巧手Ⅱ演示一下。
3、 機械系統(tǒng)
機械系統(tǒng)將描述這個手看起來如何以及有什么元件組成。它決定結(jié)構(gòu)設(shè)計、手指的數(shù)量及使用的材料。此外，還確定驅(qū)動器（如電動機）、傳感器（如位置編碼器）的位置。
3.1結(jié)構(gòu)設(shè)計
結(jié)構(gòu)設(shè)計將對機械手的靈活度起很大的作用，即它能抓取何種類型的物體以及能對被抓物體進行何種操作。設(shè)計一個機器人手的時候，必須確定三個基本要素：
·手指的數(shù)量
·手指的關(guān)節(jié)數(shù)量
·手指的尺寸和安置位置
為了能夠在機械手的工作范圍內(nèi)安全的抓取和操作物體，至少需要3根手指。為了能夠?qū)Ρ蛔ノ矬w的操作獲得6 個自由度（3 個平移和3 個旋轉(zhuǎn)自由度），每個手指必須具備3 個獨立的關(guān)節(jié)。這種方法在第一代卡爾斯魯厄靈巧手上被采用過。但是，為了能夠重抓一個物體而無需將它先釋放再拾取的話，至少需要4 根手指。
要確定手指的尺寸和安置位置，可以采用兩種方法：
·擬人化
·非擬人化
然后將取決于被操作的物體以及選擇何種期望的操作類型。擬人化的安置方式很容易從人手到機器人手的轉(zhuǎn)移抓取意圖。但是每個手指不同的尺寸和不對稱的安置位置將增加加工費用，并且使控制系統(tǒng)變得更加復(fù)雜因為每個手指都必須分別加以控制。
對于相同手指的對稱布置，常采用非擬人化方法。因為只需加工和構(gòu)建單一的“手指模塊”，因此可減少加工費用，同時也可使控制系統(tǒng)簡化。
3.2驅(qū)動系統(tǒng)
指關(guān)節(jié)的驅(qū)動器對手的靈活度也有很大的影響，因為它決定潛在的力量、精度及關(guān)節(jié)運動的速度。機械運動的兩個方面需加以考慮：
·運動來源
·運動方向
在這方面，文獻里描述了有幾種不同的方法，如文獻[3]中說運動可由液壓缸或氣壓缸產(chǎn)生，或者正如大部分情況一樣使用電動馬達(dá)。在大多數(shù)情況下，運動驅(qū)動器（如電動機）太大而不能直接與相應(yīng)的指關(guān)節(jié)結(jié)合在一起，因此，這個運動必須由驅(qū)動器（一般位于機器臂最后的連接點處）轉(zhuǎn)移過來。有幾種不同的方法可實現(xiàn)這種運動方式，如使用鍵、傳動帶以及軟軸。使用這種間接驅(qū)動指關(guān)節(jié)的方法，或多或少地降低了整個系統(tǒng)的強度和精度，同時也使控制系統(tǒng)復(fù)雜化，因為每根手指的不同關(guān)節(jié)常常是機械地連在一起，但是在控制系統(tǒng)的軟件里卻要將它們分別獨立控制。由于具有這些缺點，因此小型化的運動驅(qū)動器與指關(guān)節(jié)的直接融合就顯得相當(dāng)必要。
3.3傳感系統(tǒng)
機器手的傳感系統(tǒng)可將反饋信息從硬件傳給控制軟件。對手指或被抓物體建立一個閉環(huán)控制系統(tǒng)是很必要的。在機器手中使用了3 種類型的傳感器：
·手爪狀態(tài)傳感器確定指關(guān)節(jié)和指尖的位置以及手指上的作用力情況。知道了指尖的精確位置將使精確控制變得可能。另外，知道手指作用在被抓物體上的力，就可以抓取易碎物件而不會打破它。
·抓取狀態(tài)傳感器提供手指與被抓物體之間的接觸狀態(tài)信息。這種觸覺信息可在抓取過程中及時確定與物體第一次接觸的位置點，同時也可避免不正確的抓取，如抓到物體的邊緣和尖端。另外還能觀察覺到已抓物體是否滑落，從而避免物體因跌落而損壞。
·物體狀態(tài)或姿態(tài)傳感器用于確定手指內(nèi)物體的形狀、位置和方向。如果在抓取物體之前并不清楚這些信息的情況下，這種傳感器是非常必要的。如果此傳感器還能作用于已抓物體上的話，它也能控制物體的姿態(tài)（位置和方向），從而監(jiān)測是否滑落。
根據(jù)不同的驅(qū)動系統(tǒng)，有關(guān)指關(guān)節(jié)位置的幾何信息可以在運動驅(qū)動器或直接在關(guān)節(jié)處測量。例如，如在電動機和指關(guān)節(jié)之間有一剛性聯(lián)軸器，那么就可以用電機軸上的一個角度編碼器（在齒輪前或齒輪后）來測量關(guān)節(jié)的位置。但是如果此聯(lián)軸器剛度不夠或者要獲得很高的精度的話，就不能使用這種方法。
3.4 卡爾斯魯厄靈巧手Ⅱ的機械
系統(tǒng)為了能夠獲得如重抓等更加復(fù)雜的操作，卡爾斯魯厄靈巧手Ⅱ（KDHⅡ）由4 根手指組成，且每根手指由3 個相互獨立的關(guān)節(jié)組成。設(shè)計該手是為了能夠在工業(yè)環(huán)境中應(yīng)用（圖2 所示）和操縱箱、缸及螺釘螺帽等物體。因此，我們選用四個相同手指，將它們作對稱、非擬人化裝置，且每個手指都能旋轉(zhuǎn)90°（圖3 所示）。
圖2：裝在一個工業(yè)機器人上的KDH Ⅱ
圖3： KDH Ⅱ的俯視圖
圖4：KDH Ⅱ的側(cè)視圖
鑒于從第一代卡爾斯魯厄靈巧手設(shè)計中得到的經(jīng)驗，比如因傳動帶而導(dǎo)致的機械問題以及較大摩擦因數(shù)導(dǎo)致的控制問題，卡爾斯魯厄靈巧手Ⅱ采用了一些不同的設(shè)計方案。每根手指的關(guān)節(jié)2 和關(guān)節(jié)3 之間的直流電機被整合到手指前部肢體中（圖4 所示）。這種布置可使用很硬的球軸齒輪將運動傳遞到手指的關(guān)節(jié)處。處在電機軸上的角度編碼器（在齒輪前）此時可作為一個精度很高的位置狀態(tài)傳感器。
為了感知作用在物體上的手指力量，我們發(fā)明了一個6 維力矩傳感器（圖5 所示）。這個傳感器可當(dāng)作手指末端肢體使用，且配有一個球形指尖。它可以抓取較輕的物體，同時也能抓取3~5kg 相近重量的物體。此傳感器能測量X、Y 和Z 方向的力及繞相關(guān)軸的力矩。另外，3 個共線的激光三角測量傳感器被安置在KDHⅡ的手掌上（圖4 所示）。因為有3 個這樣的傳感器，因此不僅可以測量3 個單點之間的距離，如果知道物體的形狀，還能測出被抓物體表面之間的距離和方向。物體狀態(tài)傳感器的工作頻率為1HZ，它能檢測和避免物體的滑落。
圖5：用于KDH Ⅱ指尖的6 維力矩傳感器
4、 控制系統(tǒng)
機器人手的控制系統(tǒng)決定哪些潛在的靈巧技能能夠被實際利用，這些技能都是由機械系統(tǒng)所提供的。如前所述，控制系統(tǒng)可分為控制計算機即硬件和控制算法即軟件。
控制系統(tǒng)必須滿足以下幾個的條件：
·必須要有足夠的輸入輸出端口。例如，一具有9 個自由度的低級手，其驅(qū)動器至少需要9 路模擬輸出端口，且要有9 路從角度編碼器的輸入端口。如再加上每個手指上的力傳感器、觸覺傳感器及物體狀態(tài)傳感器的話，則端口數(shù)量將增加幾倍。
·需具備對外部事件快速實時反應(yīng)的能力。例如，當(dāng)檢測到物體滑落時，能立即采取相應(yīng)的措施。
·需具備較高的計算能力以應(yīng)對一些不同的任務(wù)。如可以對多指及物體并執(zhí)行路徑規(guī)劃、坐標(biāo)轉(zhuǎn)換及閉環(huán)控制系統(tǒng)等任務(wù)。
·控制系統(tǒng)的體積要小，以便能夠?qū)⑵渲苯蛹傻讲僮飨到y(tǒng)當(dāng)中。
·在控制系統(tǒng)與驅(qū)動器及傳感器之間必須要電氣短接。特別是對傳感器來說，若沒有的話，很多的干擾信號將會干擾傳感器信號。
4.1控制硬件
為了應(yīng)對系統(tǒng)的要求，控制硬件一般分布在幾個專門的處理器中。如可通過一個簡單的微控制器處理很低端的輸入輸出接口（馬達(dá)和傳感器），因此控制器尺寸很小，能輕易地集成到操作系統(tǒng)中。但是較高水平的控制端口則需要較高的計算能力，且需要一個靈活實時操作系統(tǒng)的支持。這可以通過PC 機輕易地解決。
因此，控制硬件常有一個非均勻的分布式計算機系統(tǒng)組成，它的一端是微控制器，而另一端則是一個功能強大的處理器。不同的計算單元則通過一個通信系統(tǒng)連接起來，比如總線系統(tǒng)。
4.2控制軟件
機器人手的控制軟件是相當(dāng)復(fù)雜的。必須要對手指進行實時及平行_控制，同時還要計劃手指和物體的新的軌跡。因此，為了減少問題的復(fù)雜性，就有必要將此問題分成幾個子問題來處理。
另一方面涉及軟件的開發(fā)。機器人手其實是一個研究項目，它的編程環(huán)境如用戶界面，編程工具和調(diào)試設(shè)施都必須十分強大和靈活。這些只能使用一個標(biāo)準(zhǔn)的操作系統(tǒng)才能得到滿足。在機械人中普遍使用的分層控制系統(tǒng)方法都經(jīng)過了修剪，以滿足機械手的特殊控制要求。
圖6：KDH II 的控制硬件架構(gòu)
4.3 卡爾斯魯厄靈巧手Ⅱ的控制系統(tǒng)
如在4.1 節(jié)中所說，對于卡爾斯魯厄靈巧手Ⅱ的控制硬件，采用了一種分布式方法（圖6 所示）。一個微控制器分別控制一個手指的驅(qū)動器和傳感器，另外一個微控制器用于控制物體狀態(tài)傳感器（激光三角傳感器）。這些微控制器（圖6 左側(cè)和右側(cè)的外箱）直接安裝在手上，所以可以保證和驅(qū)動器及傳感器之間較短的電器連接。
這些微控制器都是使用串行總線系統(tǒng)CAN 和主控計算機連在一起的。這個主控計算機（圖6、圖7 中的灰色方塊）是由六臺工業(yè)計算機組成的一個并行計算機（PC104 標(biāo)準(zhǔn)）。這些電腦都被排列在一個二維平面。相鄰電腦模塊（一臺電腦最多有8 個相鄰模塊）使用雙端口RAM 進行快速通信（圖6 中暗灰色方塊所示）。一臺電腦用于控制一個手指，另一臺用于控制物體狀態(tài)傳感器及計算物體之間的位置。其余的電腦被安裝在前面提到的電腦的周圍。這些電腦用于協(xié)調(diào)整個控制系統(tǒng)?？刂栖浖慕Y(jié)構(gòu)反映了控制硬件的架構(gòu)。如圖8 所示。
圖7：用于控制KDH II 的并行計算機
圖8：KDH II 本地控制系統(tǒng)
一個關(guān)于此手控制系統(tǒng)的三個最高層的網(wǎng)上計劃正在規(guī)劃。理想的物體位移命令可由優(yōu)越的機器人控制系統(tǒng)得到，并可用作物體路徑的精確規(guī)劃。根據(jù)已生產(chǎn)的目標(biāo)路徑就可規(guī)劃可行的抓取行為（手指作用在物體上的可行抓取位置點）?，F(xiàn)在知道了物體的運動計劃，就可以由手指路徑規(guī)劃得出每個手指的運動軌跡，并傳遞給系統(tǒng)的實時能力部分。如果一個物體被抓取了，那么其手指的運動軌跡就
傳給了物體的狀態(tài)控制器。這個控制器控制物體的姿態(tài)，它由手指和物體狀態(tài)傳感器所決定，用以獲得所需的物體姿態(tài)。如果一個手指沒有跟物體接觸，那么它的移動路徑將會直接傳遞給手控制器。這個手控制器將相關(guān)的預(yù)期手指位置傳遞給所有的手指控制器，以協(xié)調(diào)所有手指的運動。這些在手指傳感器的幫助下又反過來。
Mechanical System and Control System of a Dexterous
Robot Hand
Dirk Osswald, Heinz W?rn
University of Karlsruhe
Department of Computer Science
Institute for Process Control and Robotics (IPR)
Engler-Bunte-Ring 8 - Building 40.28
D-76131 Karlsruhe
Abstract: In recent years numerous robot systems with multifingered grippers or hands have been
developed all around the world. Many different approaches have been taken, anthropomorphic and non-anthropomorphic ones. Not only the mechanical structure of such systems was investigated, but also the necessary control system. With the human hand as an exemplar, such robot systems use their hands to grasp diverse objects without the need to change the gripper. The special kinematic abilities of such a robot hand, like small masses and inertia, make even complex manipulations and very fine manipulations of a grasped object within the own workspace of the hand possible. Such complex manipulations are for example regrasping operations needed for the rotation of a grasped object around arbitrary angles and axis without depositing the object and picking it up again. In this paper an overview on the design of such robot hands in general is given, as well as a presentation of an example of such a robot hand, the Karlsruhe Dexterous Hand II. The paper then ends with the presentation of some new ideas which will be used to build an entire new robot hand for a humanoid robot using fluidic actuators.
Keywords: Multifingered gripper, robot hand, fine manipulation, mechanical system, control system
1 Introduction
The special research area 'Humanoid Robots' founded in Karlsruhe, Germany in July 2001 is
aimed at the development of a robot system which cooperates and interacts physically with human
beings in 'normal' environments like kitchen or living rooms. Such a robot system which is
designed to support humans in non-specialized, non-industrial surroundings like these must, among
many other things, be able to grasp objects of different size, shape and weight. And it must also
be able to fine-manipulate a grasped object. Such great flexibility can only be reached with an
adaptable robot gripper system, a so called multifingered gripper or robot hand.
The humanoid robot, which will be built in the above mentioned research project, will be equipped
with such a robot hand system. This new hand will be built by the cooperation of two institutes, the
IPR (Institute for Process Control and Robotics) at the University of Karlsruhe and the IAI (Institute
for Applied Computer Science) at the Karlsruhe Research Center. Both organizations already have
experience in building such kind of systems, but from slightly different points of view.
The 'Karlsruhe Dexterous Hand II' (see figure 1) built at the IPR, which is described here in detail, is
a four fingered autonomous gripper. The hands built at the IAI (see figure 17) are built as prosthesis for handicapped people.
The approach taken so far will be presented and discussed in the following sections, as it founds the
basis for the novel hand of the humanoid robot.
Figure 1: Karlsruhe Dextrous Hand II from IPR
2 General structure of a robot hand
A robot hand can be split up in two major subsystems:
? The mechanical system
? The control system
The mechanical system, further described in section 3, can be subdivided into:
- The mechanical design
- The actuator system
- The sensor system
And the control system described in section 4 consists at least of :
- The control hardware
- The control software
For each of these parts we will describe the considerations for a robot hand in general and then
present the exemplary implementation in the Karlsruhe Dexterous Hand II.
3 Mechanical system
The mechanical system describes how the hand looks like and what kind of components it is made
of. It defines the mechanical design, e.g. the number of fingers and the kind of materials used.
Additionally actuators, e.g. electric motors, and sensors, e.g. position encoders, are settled.
3.1 Mechanical design
The mechanical design determines the fundamental 'dexterousness' of the hand, i.e. what kind of
objects can be grasped and what kind of manipulations can be performed with a grasped object. Three basic aspects have to be settled when designing a robot hand:
? The number of fingers
? The number of joints per finger
? The size and placement of the fingers
To be able to grasp and manipulate an object safely within the workspace of the hand at least 3 fingers are required. To achieve the full 6 degrees of freedom (3 translatory and 3 rotatory DOF) for the
manipulation of a grasped object at least 3 independent joints are needed for each finger. This approach was taken for the first Karlsruhe Dexterous Hand [1,2]. However, to be able to regrasp an object without having to release it and then pick it up again, at least 4 fingers are necessary.
To determine the size and the placement of the fingers two different approaches can be taken:
? Anthropomorphic
? Non-anthropomorphic
It then depends on the objects to manipulate and on the type of manipulations desired which one is
chosen. An anthropomorphic placement allows to easily transfer e.g. grasp strategies from a human
hand to the robot hand. But the different sizes of each finger and their asymmetric placement makes
the construction more expensive and the control system more complicated, because each finger has
to be treated separately. When a non-anthropomorphic approach is taken most often identical fingers are arranged symmetrically. This reduces the costs for the construction and simplifies the control system because there is only one single 'finger module' to be constructed and controlled.
3.2 Actuator system
The actuation of the finger joints also has a great influence in the dexterousness of the hand, because
it determines the potential forces, precision and speed of the joint movements. Two different aspects of the mechanical movement have to be considered:
? Movement generation
? Movement forwarding
Several different approaches for these aspects are described in the literature. E.g. the movement can
be generated by hydraulic or pneumatic cylinders [3] or, as in most cases, by electric motors.
As the movement generators (motors) are in most cases to big to be integrated in the corresponding
finger joint directly, the movement must be forwarded from the generator (most times located in the last link of the robot arm) to the finger joint. Again different methods can be used, like tendons
[4,5,6], drive belts [1,2] or flexible shafts. The use of such more or less indirect actuation of the finger
joint reduces the robustness and the precision of the system and it complicates the control system
because different joints of one finger are often mechanically coupled and must be decoupled in
software by the control system. Due to these drawbacks an integration of miniaturized movement generators directly into the finger joints is desirable.
3.3 Sensor system
The sensor system of a robot hand provides the feedback information from the hardware back to
the control software. This is necessary to perform a closed loop control of the fingers or a grasped
object. Three types of sensors are used in robot hands [7,8]:
? Gripper state sensors determine the position of the finger joints, and hence the finger tip, and
the forces which act upon the finger. Knowing the exact position of the fingertip makes precise
position control possible, which is necessary for dexterous fine manipulations. With the knowledge of the forces applied to a grasped object by the fingers it is possible to grasp a fragile object without breaking it.
? Grasp state sensors provide information about the contact situation between the finger and the object. This tactile information can be used to determine the point in time of the first contact with the object while grasping, and to avoid undesired grasps, like grasping at an edge or a tip of the object. But it can also be used to detect slippage of an already grasped object, which might lead to a loss of the object.
? Object state or pose sensors are used to determine the shape, position and orientation of an object in the workspace of the gripper. This is necessary if these data is not known exactly, prior to grasping the object. If the object state sensors still works on a grasped object it can be used to control the pose (position and orientation) of a grasped object too, e.g. to detect slippage.
Depending on the actuator system the geometrical information about the finger joint position can be
measured at the movement generator or directly at the joint. For example if there is a stiff coupling
between an electric motor and the finger joint then the joint position can be measured by an angle
encoder at the axis of the motor (before or after the gear). This is not possible if the coupling is less
stiff and a high position precision is desired.
Figure 2: KDH II mounted on an industrial robot
圖3： KDH Ⅱ的俯視圖
圖4：KDH Ⅱ的側(cè)視圖
3.4 The mechanical system of the Karlsruhe
Dexterous Hand II
In order to permit more complex manipulations like regrasping the current Karlsruhe Dexterous Hand II(KDH II) was built with 4 fingers and 3 independent joints per finger. It is designated for applications in industrial environments (see figure 2) and for manipulation of objects like boxes, cylinders, screws or nuts. Therefore a symmetric, non-anthropomorphic configuration of four identical fingers, each rotated by 90° was chosen (see figure 3).
Due to the experiences gained with the first Karlsruhe Dexterous Hand, like e.g. mechanical
problems caused by the drive belts or controlling problems caused by large friction factors, some
different design decisions were chosen for the KDH II. The dc-motors for joint 2 and 3 of each
finger are integrated into the previous finger limb (see figure 4). This permits the use of very stiff
ball-spindle-gears for the forwarding of the movement to the finger joint. Angle encoders directly on the motor axis (before the gear) are used as very precise position state sensors.
For sensing the forces applied to an object by a finger a prototype of a 6 dimensional force torque
sensor has been developed (see figure 5). It can be used as the last finger limb and is equipped with a
spherical finger tip. It is able to grasp light objects as well as relatively heavy objects up to 3 to 5 kg.
The sensor is able to measure forces in x- y- and zdirection and torques around these axes. Additionally 3 colinear laser triangulation sensors are mounted in the palm of the KDH II (see figure 4) [11]. Because there are three such sensors not only the distances of 3 single points can be measured, but also the distance and orientation of the surface of a grasped object, if the shape of the object is known. This object pose sensor works with a frequency of 1 kHz which allows the detection and avoidance of a slipping object.
4 Control system
The control system of a robot hand determines which of the potential dexterous skills provided by
the mechanical system can actually be exploited. As mentioned before the control system can be
subdivided in the control computer or hardware and the control algorithms or software.
The control system must meet several conflicting requirements:
Figure 5: 6 DOF force torque sensor with strain gage sensors used as the last finger limb of the KDH II
? Many input/output resources like actor or sensor signals must be attached. For example for a minimum hand with 9 degrees of freedom, at least 9 analog outputs to the motors and 9 inputs from angle encoders must be estimated. With force and tactile sensors for every finger and additional object state sensors the number of inputs quickly increases to several dozens.
? Quick reactions in real-time to external events are required. If for example a slipping of the grasped object is detected immediate counter measures must be taken.
? High computing power for several different tasks must be available. For example path planning, coordinate transformations, closed loop control in software are executed in parallel for multiple fingers as well as for the object.
? Small physical size is needed to be able to integrate the control system into the manipulation system.
? Short electrical connections between the control system and the actuators and sensors should be
used. This is especially relevant for the sensors because otherwise massive interference might disturb the sensor signal.
4.1 Control hardware
To cope with the requirements the control hardware is usually distributed among several specialized
processors. For example the input/output on the lowest level (motors and sensors) can be handled by a simple microcontroller, which is also of small size and thus can be integrated more easily into the
manipulation system. But the higher levels of control need more computing power and the support of a flexible real time capable operating system. This can be achieved most easily with PClike components.
Therefore the control hardware often consist of a non-uniform, distributed computing system with
microcontrollers on the one end and more powerful processors on the other. The different computing
units then have to be connected with a communication system, like for example a bus system.
4.2 Control software
The control software of a robot hand is quite complex. Several fingers must be controlled in realtime
and in parallel while new trajectories for the fingers and the object must be planned at the same time. Therefore it is necessary to reduce the complexity by dividing the problem into sub problems.
Another aspect concerns software development. As a robotic hand is usually a research project for most of it's lifetime, the programming environment, like user interface, programming tools and debugging facilities, should be powerful and flexible. This can only be achieved if a standard operating system is used.
Figure 6: control hardware architecture of the KDH II
The usual hierarchical control system approach used in robotics has to be trimmed to fit the special
needs of the controlling of a robot hand.
4.3 The control system of the Karlsruhe
Dexterous Hand II
As suggested in section 4.1 a distributed approach to the control hardware was taken for the Karlsruhe Dexterous Hand II (KDH II) (see figure 6) [8]. One microcontroller is used to control the actuators and sensors of one finger respectively. An additional microcontroller is used for the object state sensor (laser triangulation sensors). These microcontrollers (the outer boxes to the left and right in figure 6) are mounted directly on the hand, thus short electrical connections to the actuators and sensors are guaranteed. The microcontrollers are connected to the main control computer by serial bus systems (CAN-bus).
The main control computer of the KDH II (the light grey box in figure 6, and figure 7) is implemented as a parallel computer consisting of 6 industrial PCs (PC104 standard). These PCs are arrang