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Positioning Fault Detection of a Piezoelectric-Driven Microrobot
Copyright ID IFAC Fault Detection, Supervision and Safety for Technical Processes, Kingston Upon Hull, UK, 1997
POSITIONING FAULT DETECTION OF A PIEZOELECTRIC-DRIVEN MICROROBOT F. Dumolltier, K. Santa and S. Fatikow
Univcrsity of J(aT"l.sruhe In.stitntc for' R('.nl- Time Computer Sy.stcm.s and Robotics D-76128 Kndsm/tc. Ge1many Phone: +49-721-6()8-4252, Fax: +49-721-606-740 emflil: dumont@im. uka. de
Abstract: l\licromanipulation has hecome an issue of primary importance in industry and biomedicine, the manual capabilit.ies being restricted to certain tolerances. For example manipulat.ion of biological cells or an assembly of a whole microsystem composed of different microcomponcnts have to be carried out by piezo electricallydriven microrobots. For this rcason, an automated microrobot-based micromanipulation station is developed by all int.enlisciplinary group at the Universit.y of Karlsruhe. The process of assembly takes place in the field of view of a light optical microscope. The principal sensors of t.he syst.em are CCD cameras. One of them, coupled with the microscope, is the local sensor that. allows the automation of the manipulation process under the microscopc. A sccond one, the global sensor, supervises the entire system. In this work we present. t.he first step of a method for the detection of faults occurring during the mauipulat.ion process. This first stage consists of detecting and processing a positioll deviation of t.he microrobot. Copyright ID 1998 IFAC Keywords: microrobotic, sensor systcm, monitoring, positioning analysis
1. INTRODUCTION
using the parallel computer system (CIG7 microcOlltrollers). Wit.h t.he mllltiproccssor systcm, the generat.ed cOlllmands can be executed in parallel, which makes the microassembly station of rcalt.ime behaviour. In order to be able to control the manipulation processes in the microassembly stat.ion, there must be a feedback which is generated by the two t.ypes of sensors described in thc next section.
The schf'matic design of t.he micromanipulat.ion st.at.ion can be seen in Fig. 1 (Fatikow ;llld Ill'lIlbold 1996). l'vlicrorobots are operat.ing 011 t.he plat.form under a light-optical microscope (Sallt.a et al. 1996). The microscope is full aut.unwtahle wit.h t.he help of a IlS232 standard interface. The lIlotiOIl of the table, the light int.ensit.y as well as t.he challge of the objectives call he cOlltrollcd alltolllatically. III particular the vcrtical ami horizontal position of the table call bc kllowlI wit.h " high accuracy. The higher control level of thc statioll, a central comput.er (Pent.iuUl PC), asS11l11('S t.he image processing algorit.hms, t.he t.ask of task-specific assembly planlling, to define ,,11 tlw lIccessary steps, which are carried 011t. successivdy. The cOlllmands of the central comput.er are t.ll(~lI fmther processed on a lower cOllt.rul level,
2. DESCRIPTION OF THE SENSOR SYSTEl'vr The sensor system (Fischer et al. 1996) is subdivided into a local and a global sensor system. The camera and the microscope form t.he local sensor s.ystem and a global CCD camera or/and a lascr distance meter form the second olle. 651
.-
-
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-
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Cont ro l algorith ms for - microrobots - microscope
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Fig_ 1. Oyerview of the micromanipulat.ion station 2.1 The yio/}(L[ .sen.sm·
The glohal sensor system has Leen implemented t,o deterllline the position amI orientation of the llIicrorohots 011 t.he stage of the microscope. Two fixed points on the top of each microrobot. platfortll are sufficient to calculate their position and orientation. This points can he located by two difff'rent methods: • each point is marked Ly a light emitting cOlllponent. (e.g. LED, see Fig 2) . At the hegillning of the motioll position and orientat.ion of the microrobot are determilled hy the detection of the three LEDs with the help of t,he camera which has been calibrated hefore. D1ll'ing a motion only two LEDs are tracked hy the camera. • two light detectioll sensors are placed on t.he top of t he llIirrorouot and a rotating laser 1)(';tm is scanning the stage. Thus. the position of the sensors is given Ly the position of the laser when the laser Leam is detected . In both cases , the orientation of the microrobot is given b.y the vector of the straight line hetweell the first and the second refert'nce point.
Fig. 2. MINIl'vIAN , one of the microrobot on the microscope specimen stnge from the CCD-carnera image by an image recognition system. The following method can ue used to obtain depth information of these objects: A laser-spot (not shown in Fig. 1) is projected with a fixed angle onto the objects. FrolIl the position of the laser reflection the height of the object can be calculated. The position of the endeffector tip eau also Le determined by this measuring method. Another possibility for the recogllition of the eudeffector is the use of optical fiber cables fixed (e.g. glued) to the tip of the tool. The light emitted at the end of the fiber call be seen by the camera. Thus, the position of the Jight-poillt alld the correspondillg tool call be determined .
2.2 The local sensor' .system
The posit,ion of the objects to be manipulated in the yiewing area of t.he microscope is determined 652
3. PRINCIPLE OF THE ROBOT l'vIOTION
XO. This last actuation is carried out relatively slowly, to keep the legs from sliding on the glass base. In the simplified motion algorithm in Fig. 5b, contrary to the first met.hod, the legs a.re not lift.ed, but they slide on the surface. The price for t.his simpler movement is the unstahle platform motioIl, which is very dependent 011 the robot mass. These two descriptions point out that the leg motion is very sensitive to the nature ami the state of the surface. For example a small crack on the surface can perturb the motion of one leg and t.his is one of the faults that must be detected and located.
3.1 Description of the leg motion
The positioning system of t.he microrobot consists of three triaugularly arranged piezo actuators (sec Fig. 3). With piezoelect.ric legs, the lIIicrorobot can perform" small" movcmcnts, in the JIInrllllgC , as well as "Iarge" ones, in the cm rallge (l\Iagnllssen et al. 1995).
b)
Platform moti4
Leg motion
--.
I Tlcw=~r::r -~ . - ~~- I
I'iewcieclricaiiegs
Fig. 3. Piezo positioning syst.em : a)Top view; b )front view
-
The picmactuators are piezoccralllic tubes (see Fig. 4) l'quipped with an inner aud four outer electrodes (Munassypov et al. 199G). By applying voltages between the inner alld one of the out.cr elcctrodes the piezoceramic material in t.his area changes its length. This principlc is used to lellgthcn, shorten and to bend t.he piew If'g in dther direction.
i
"I"
:"(0
x()
xO
i
xO x t
)(0
", X
I
a.
b.
Fig. 5. Leg-control for the robot motioIl
Inner electrode 3.2 Description of a manipulation pT'Ocess
A manipulation process can be described as follows: the microrobot, more precisely its mauipulators, ami the objects must be placed together in the field of view of the microscope. A robot walks on the table of the microscopc towards the microobjects which have to be manipulated , the manipulat.ors are placed close to these with an accuracy of less than 3 or 4 nUll (the dimension of t.he largest possible image taken by the microscope camera) and then all of them are brought together under the microscope, with the help of the aut.omated table, where the local sensor can take t.he process over. The type of the microrobot motion chosen is a combination of a rotat.ion a.round the leg number 2 (see Fig. 3) with a translation movement. For each leg, the direction of bending (defined with xi/oc and yi/ oc ) ami the relative speeds s]Jccdi are calculated (see Fig. G). A speed (which takes values between 0 and 255) corresponds to the frequency of the leg bending that has been described before.
Outer electrodes Fig. 4. Piezoceramic tube actuator Fig. !j shows two possible motion nl0.t.hocls for t.he robot platform (Fatikow 1995). The mot.ion ill Fig. 5a is basically divided into four steps. At. t.he beginning, no voltage is applied to t.he ]>ip;~()ccralUics. In order to chauge posit.ioll, the legs are first. relatively slowly bent. so that they stay ill wlltact with the base. The platform is "taken away" ami moves a lit.tle in t.he desired direction. Then, the voltage polarizat.ions on the actuator electrodes are suddenly changed, so that all t.hree legs bend quickly in the opposit.e direct.ioll. In order to preyent sliding friction bctween t.he legs ami the bClse, the robot lift.s all three legs at. once. The bent. legs then laud in t.heir ne\\' posit.ion, whereby the platform does not change its posit.ion. Aft.erwards, the legs st.raight.en out and t.he platform moves a little more in t.hc desired direction, thereby taking the step ilX = X 1 653
End position and orientation
Start position and orientation (used at the beginning of the 1111ltion) •
Calculation of the directions:
Yb
,.--..
Xh
....
Xo
I
YO
I
nO
I I
I
L\X
-
rI
L\Y
-
L\a I
-
Calculation of the direction of the motion dir in the local coordinate system of a leg
~ .YAx', •.,2~' • m~IS.L) L = l!.!...!..lll!. 360
. for the leg i= I and 3 : xiloc = xdir (S.z) + xirot(L.Z) yiloc = Ydir (S.Z) + yirot(L.Z) . for the leg i=2: x210c = xdir and y 2 10c = Ydir Calculation of the ~~ed for each IC2: MDS = max(DSi. i= 1.3) with DSi = sqrt(xiloc2 + yiloJ) for i=I.3 : speedi = (DSi I MDS). 255
(la Ya Xa
Determination of the current position and orientation
I I
Motion
I
Fig. G. Calculation of the paramet.er for the wutrol of the microrobot
4. SUPERVISION OF THE MICROROBOT MOTION
the legs (the orieut.ation of the electrodes of each leg should be the same). Moreover the velocity of the microrobot is not proportional to the speed of the leg motion (see Fig 8). This results frolll the princip of the leg motion based upon the friction between the leg nllti t.he surface • an uncertain disturbance due to a default with the surface a..<; it has been explained ill section 3.1.
4 .1 Mic1"Ombot fault analysis
n.,·
usiug the control loop shown iu Fig. G, the trajectory is not the desired OIlC . Fig. 7 shows au example for the deviation bctweeu t.he real t.rajectury and the theoretical one. At. first t.he lllicrorohot rot.ates arouud t.he leg ulllllber 2 Ilnt.il its orieut.at.ion is t.he same as the cud ori(mt.at.ion, t.hen it. walks in the direction of t.he end point..
2.6
~
~
2
E
.s Co
'u 0
1.5
v >
100 150 200 Speed (leg oscillation) ~
250
Fig. 8. Velocity of the microrobot versus the speed of the leg motion
Rotation
Fig. 7. Trajectory of the legs aud the deviatiou Two t.\·pes of dist.urbances act. upou t.he lIIicrorohot.:
4.2 Description of the system
• a systematic or intrinsic error that leads t.o a ('oust.ant. deviation. It is due ou ouc hami to a dilTerence in t.he manufact.ure of t.he t.hree legs (t.he surface of the electrode or t.he length of t.he legs could be different) ami 011 the other haud to an inevitahle different. posit.iouing of
The goal of this work is to design a fault identification process for the deviat.ion of the microrobot. during a motion . This process must be incorporated into the normal control loop. One approach of a fault dct.ectioll process is a Illodel-based approach (Patton 1994) in which a 654
residual signal is h.uilt up having a scnsitidt.y t.o a 'he block diagram of the general struct.ure fall It.. 1 appears in Fig. 9.
Fault decision logic "t''residual k\ ", , -- - - ,
Fig. 10. Generation of the resit.lual for the deviation analysis
Residual generation
4.3 Deviation Analysis faults
Input
System
The deviation analysis process must ue able to distinguish the systematic errors from the uncert.ain disturbances. One way to do this is to integrate these errors in the microrobot model. As already mentioned the model complexity is too high to be calculated easily. Another way is to realize an on-line learning-and-adaptation approach usiug a neural network that can learn the most coutrol problems aud compensate the systematic disturbance. The input parameters of the neural network are the calculated trajectory, the actual control paramcters from the controller aud the actual positiou of the microrobot. Another possibility is the use of a fuzzy-logic. In this case, the fuzzy-controller which receives the difference between the calculated aud t.he real position ac; input parameter, acts directly upon the controller. The rule base of the fuzzy coutroller contains the ap7'io7'i kuowledge about. the behaviour of t.he microrobot.
Output
fi!!;. 9. Geucral st.ructure of a model-based fault diagnosis
fi!!; . 10 illustrates the case of t.he lllicrorobot syst.em t.hat can Le described wit.h the foIIowillg st.ate equations:
;Ck+1
= I(Xk, Uk, Iu)
Yk+l
= g(;r~,)
At the moment the deviat.ion a.nalysis uses the residual that coutains the iuforl11ation about the position of each leg as well as the dynamic state of the microrobot. The speed of the legs (see Fig. 11) is compared with the input speeds (frequency used for the leg motion). A too important disparity between these two values could indicate a perturbation with a faulty leg or with the part of the surface the leg moves 011.
:r~. represents t.he state vector at. the k-th sampling instaut ali(I is defilled by the co-ordinates of t.he Ipgs of the microrobot amI the angle orientatiou. 111: iu the input vector defined Ly the parameters gi\'en to the systel11 control: the speed and t.he direction of the mot.ion aud this for each leg. I.. are Ill(' s.\·st,Plllatic disturbances and III are the Iluccrtaiu distmiJances. The gloLal seusor (CCD camera) lllPasures the state YI, of the microrobot. wit.h the help of a calibratiou met.hod (fuuct.iou fJ)wich gin'S t.he relationships Let.weell image coordinates and \vorld coordinates. The input parameter 1(1 of t.he systcm is the position of the lIlicrorobot. The llIathematicalmodel of the lllicrorobot. t.
5. CONCLUSIONS AND FUTURE WORKS This paper presented the positioning fault detection of a microrobot in a micromanipulation station. The automation of this st.ation beiug the main goal of the project, several sensors system are used and a fault. diaguosis is ueeded to locat.e different kinds of faults . A first approach \vas the fault occurring during the positioning of a microrobot which is very sensit.ive to the surface it moves OIl. Future work deals with a better understanding of the rouot motion (improvement of the robot lIlodel) and the implementation of the mcthods for the compensatiou of the systematic 655
t >
Fischer, T ., K. Sauta and S. Fatikow (1996). System and powerful cumputer system for COli trolling a microrobot-based micromanipulation station. In: Mic1'OmechaTlics Enrollc, Bar·celona. pp. 283- 286. Magnussen, B. , S. FatikO\v and U. Rembold (1995). Actuation in mic1'Osystems: Problem field overview and practical example of the piezoelectric robot for handling of lIlicroobjects. In: Pmc. ETFA '95, Emc7ging Tcclmologics and FactoT'Y A utoTT!ation, Paris. Vo!. 3. pp. 21- 27. ]'Vlunassypov, R., B. Grossmaull, B. Magnussen and S. Fatikow (1996) . Development and control of piezoelectric actuators for a mobile micromanipulation system. In: Actuator 96 Int. ConJ. on News Actnactor's, Brcmen. pp. 213216. Patton, Ron .1. (1994) . Robust model-based fault diagnosis: the state of the art. In: Fault dctcction, supervision and .safcty for tcchnical pmcesscs, IFAC Symposinm. pp. 1-24. Santa, K., I3. Magnusseu ami S. Fatikow (1996). Miniroboter fiir prazisionsarbeit. Iu: Fcinwcrktcchnik, Mik7'Otcchnik, Mik1'Oelckt1'Ouik. Vo!. 9. pp. 632-634.
Leg 1
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ii '
c--~~-------
s
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Time (5)
' 'is " '18.9
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: c __-
00
5
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'l
IS
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Fig. 11. Evolution of the yelocity of each leg dmiug it displacement. dn·iat.ion (neuraluetwork aud fuzzy cont.rul) . The next. step could be tu take int.o accuunt other s('nsors slIch as the loca.l sensor. l\-Iureover se\'(~ral llIicroroLots must. be used toget.her. In t.his case, tlw importance of the fault detection increases, for exalllple to avoid collisions between mic1'Orohots (\)1(1 t.o guarantee a fault-free manipulatiun p1'on'ss.
6. ACKNOWLEDGEMENTS This res(~arch work was performed at the IlIst.itute for n('a.I-Tillle Computer Systems ami Robot.ics, Prof. Dr.-lng. U. Relllbold, Prof. Dr.-lug. H. \V(il'll alld Prof. Dr.-lug. R Dilllllanll, Depart.mcllt of Compllt,pr Science, University uf KarlsrnIH> , GerIU:1I1.\:. The research is fOllnded hy tllP. EC program "HCl\I" , cont.ract IIIlmber CHRXCT940576.
7. REFERENCES Fatikow, S. (1995) . l\Iikrowbot.ik. Ill: 1'alj1L7l.slmnd des 2. W 07'ksh(1) M ethode7l.- 111/,(1 Wer·kzC11.grntwicklnng fur den Mikt·osyslernencntuI1L7j. Karslrulte. pp. 8- 18. Fatikow, S. and U. Rembold (1996). An automat.ed mic1'Orobot-based deskt.op st.at.ion for lIIicro assembly and handliug of lIIicroouj('ct.s. Ill : P7'Oc. ETFA '96, Emrr:ging Technologics /Lnd Fact07'y A uto7llation. Kana i, Ha waii. 656
POSITIONING FAULT DETECTION OF A PIEZOELECTRIC-DRIVEN MICROROBOT F. Dumolltier, K. Santa and S. Fatikow
Univcrsity of J(aT"l.sruhe In.stitntc for' R('.nl- Time Computer Sy.stcm.s and Robotics D-76128 Kndsm/tc. Ge1many Phone: +49-721-6()8-4252, Fax: +49-721-606-740 emflil: dumont@im. uka. de
Abstract: l\licromanipulation has hecome an issue of primary importance in industry and biomedicine, the manual capabilit.ies being restricted to certain tolerances. For example manipulat.ion of biological cells or an assembly of a whole microsystem composed of different microcomponcnts have to be carried out by piezo electricallydriven microrobots. For this rcason, an automated microrobot-based micromanipulation station is developed by all int.enlisciplinary group at the Universit.y of Karlsruhe. The process of assembly takes place in the field of view of a light optical microscope. The principal sensors of t.he syst.em are CCD cameras. One of them, coupled with the microscope, is the local sensor that. allows the automation of the manipulation process under the microscopc. A sccond one, the global sensor, supervises the entire system. In this work we present. t.he first step of a method for the detection of faults occurring during the mauipulat.ion process. This first stage consists of detecting and processing a positioll deviation of t.he microrobot. Copyright ID 1998 IFAC Keywords: microrobotic, sensor systcm, monitoring, positioning analysis
1. INTRODUCTION
using the parallel computer system (CIG7 microcOlltrollers). Wit.h t.he mllltiproccssor systcm, the generat.ed cOlllmands can be executed in parallel, which makes the microassembly station of rcalt.ime behaviour. In order to be able to control the manipulation processes in the microassembly stat.ion, there must be a feedback which is generated by the two t.ypes of sensors described in thc next section.
The schf'matic design of t.he micromanipulat.ion st.at.ion can be seen in Fig. 1 (Fatikow ;llld Ill'lIlbold 1996). l'vlicrorobots are operat.ing 011 t.he plat.form under a light-optical microscope (Sallt.a et al. 1996). The microscope is full aut.unwtahle wit.h t.he help of a IlS232 standard interface. The lIlotiOIl of the table, the light int.ensit.y as well as t.he challge of the objectives call he cOlltrollcd alltolllatically. III particular the vcrtical ami horizontal position of the table call bc kllowlI wit.h " high accuracy. The higher control level of thc statioll, a central comput.er (Pent.iuUl PC), asS11l11('S t.he image processing algorit.hms, t.he t.ask of task-specific assembly planlling, to define ,,11 tlw lIccessary steps, which are carried 011t. successivdy. The cOlllmands of the central comput.er are t.ll(~lI fmther processed on a lower cOllt.rul level,
2. DESCRIPTION OF THE SENSOR SYSTEl'vr The sensor system (Fischer et al. 1996) is subdivided into a local and a global sensor system. The camera and the microscope form t.he local sensor s.ystem and a global CCD camera or/and a lascr distance meter form the second olle. 651
.-
-
-
-
-
-
Local senso r system
-
,-
cc u-
camera
-
-
-
-
-
'Control ,termini\.
-
,
,
J
,
,--. ,
-
-
-
-
-
-
-
-
-
-
-
~
Cont ro l algorith ms for - microrobots - microscope
SUN -Worksl3lion Cross-compiler Debugg ing f\.licr()~COI) e
hose
A ut om.tic pl atform
Fig_ 1. Oyerview of the micromanipulat.ion station 2.1 The yio/}(L[ .sen.sm·
The glohal sensor system has Leen implemented t,o deterllline the position amI orientation of the llIicrorohots 011 t.he stage of the microscope. Two fixed points on the top of each microrobot. platfortll are sufficient to calculate their position and orientation. This points can he located by two difff'rent methods: • each point is marked Ly a light emitting cOlllponent. (e.g. LED, see Fig 2) . At the hegillning of the motioll position and orientat.ion of the microrobot are determilled hy the detection of the three LEDs with the help of t,he camera which has been calibrated hefore. D1ll'ing a motion only two LEDs are tracked hy the camera. • two light detectioll sensors are placed on t.he top of t he llIirrorouot and a rotating laser 1)(';tm is scanning the stage. Thus. the position of the sensors is given Ly the position of the laser when the laser Leam is detected . In both cases , the orientation of the microrobot is given b.y the vector of the straight line hetweell the first and the second refert'nce point.
Fig. 2. MINIl'vIAN , one of the microrobot on the microscope specimen stnge from the CCD-carnera image by an image recognition system. The following method can ue used to obtain depth information of these objects: A laser-spot (not shown in Fig. 1) is projected with a fixed angle onto the objects. FrolIl the position of the laser reflection the height of the object can be calculated. The position of the endeffector tip eau also Le determined by this measuring method. Another possibility for the recogllition of the eudeffector is the use of optical fiber cables fixed (e.g. glued) to the tip of the tool. The light emitted at the end of the fiber call be seen by the camera. Thus, the position of the Jight-poillt alld the correspondillg tool call be determined .
2.2 The local sensor' .system
The posit,ion of the objects to be manipulated in the yiewing area of t.he microscope is determined 652
3. PRINCIPLE OF THE ROBOT l'vIOTION
XO. This last actuation is carried out relatively slowly, to keep the legs from sliding on the glass base. In the simplified motion algorithm in Fig. 5b, contrary to the first met.hod, the legs a.re not lift.ed, but they slide on the surface. The price for t.his simpler movement is the unstahle platform motioIl, which is very dependent 011 the robot mass. These two descriptions point out that the leg motion is very sensitive to the nature ami the state of the surface. For example a small crack on the surface can perturb the motion of one leg and t.his is one of the faults that must be detected and located.
3.1 Description of the leg motion
The positioning system of t.he microrobot consists of three triaugularly arranged piezo actuators (sec Fig. 3). With piezoelect.ric legs, the lIIicrorobot can perform" small" movcmcnts, in the JIInrllllgC , as well as "Iarge" ones, in the cm rallge (l\Iagnllssen et al. 1995).
b)
Platform moti4
Leg motion
--.
I Tlcw=~r::r -~ . - ~~- I
I'iewcieclricaiiegs
Fig. 3. Piezo positioning syst.em : a)Top view; b )front view
-
The picmactuators are piezoccralllic tubes (see Fig. 4) l'quipped with an inner aud four outer electrodes (Munassypov et al. 199G). By applying voltages between the inner alld one of the out.cr elcctrodes the piezoceramic material in t.his area changes its length. This principlc is used to lellgthcn, shorten and to bend t.he piew If'g in dther direction.
i
"I"
:"(0
x()
xO
i
xO x t
)(0
", X
I
a.
b.
Fig. 5. Leg-control for the robot motioIl
Inner electrode 3.2 Description of a manipulation pT'Ocess
A manipulation process can be described as follows: the microrobot, more precisely its mauipulators, ami the objects must be placed together in the field of view of the microscope. A robot walks on the table of the microscopc towards the microobjects which have to be manipulated , the manipulat.ors are placed close to these with an accuracy of less than 3 or 4 nUll (the dimension of t.he largest possible image taken by the microscope camera) and then all of them are brought together under the microscope, with the help of the aut.omated table, where the local sensor can take t.he process over. The type of the microrobot motion chosen is a combination of a rotat.ion a.round the leg number 2 (see Fig. 3) with a translation movement. For each leg, the direction of bending (defined with xi/oc and yi/ oc ) ami the relative speeds s]Jccdi are calculated (see Fig. G). A speed (which takes values between 0 and 255) corresponds to the frequency of the leg bending that has been described before.
Outer electrodes Fig. 4. Piezoceramic tube actuator Fig. !j shows two possible motion nl0.t.hocls for t.he robot platform (Fatikow 1995). The mot.ion ill Fig. 5a is basically divided into four steps. At. t.he beginning, no voltage is applied to t.he ]>ip;~()ccralUics. In order to chauge posit.ioll, the legs are first. relatively slowly bent. so that they stay ill wlltact with the base. The platform is "taken away" ami moves a lit.tle in t.he desired direction. Then, the voltage polarizat.ions on the actuator electrodes are suddenly changed, so that all t.hree legs bend quickly in the opposit.e direct.ioll. In order to preyent sliding friction bctween t.he legs ami the bClse, the robot lift.s all three legs at. once. The bent. legs then laud in t.heir ne\\' posit.ion, whereby the platform does not change its posit.ion. Aft.erwards, the legs st.raight.en out and t.he platform moves a little more in t.hc desired direction, thereby taking the step ilX = X 1 653
End position and orientation
Start position and orientation (used at the beginning of the 1111ltion) •
Calculation of the directions:
Yb
,.--..
Xh
....
Xo
I
YO
I
nO
I I
I
L\X
-
rI
L\Y
-
L\a I
-
Calculation of the direction of the motion dir in the local coordinate system of a leg
~ .YAx', •.,2~' • m~IS.L) L = l!.!...!..lll!. 360
. for the leg i= I and 3 : xiloc = xdir (S.z) + xirot(L.Z) yiloc = Ydir (S.Z) + yirot(L.Z) . for the leg i=2: x210c = xdir and y 2 10c = Ydir Calculation of the ~~ed for each IC2: MDS = max(DSi. i= 1.3) with DSi = sqrt(xiloc2 + yiloJ) for i=I.3 : speedi = (DSi I MDS). 255
(la Ya Xa
Determination of the current position and orientation
I I
Motion
I
Fig. G. Calculation of the paramet.er for the wutrol of the microrobot
4. SUPERVISION OF THE MICROROBOT MOTION
the legs (the orieut.ation of the electrodes of each leg should be the same). Moreover the velocity of the microrobot is not proportional to the speed of the leg motion (see Fig 8). This results frolll the princip of the leg motion based upon the friction between the leg nllti t.he surface • an uncertain disturbance due to a default with the surface a..<; it has been explained ill section 3.1.
4 .1 Mic1"Ombot fault analysis
n.,·
usiug the control loop shown iu Fig. G, the trajectory is not the desired OIlC . Fig. 7 shows au example for the deviation bctweeu t.he real t.rajectury and the theoretical one. At. first t.he lllicrorohot rot.ates arouud t.he leg ulllllber 2 Ilnt.il its orieut.at.ion is t.he same as the cud ori(mt.at.ion, t.hen it. walks in the direction of t.he end point..
2.6
~
~
2
E
.s Co
'u 0
1.5
v >
100 150 200 Speed (leg oscillation) ~
250
Fig. 8. Velocity of the microrobot versus the speed of the leg motion
Rotation
Fig. 7. Trajectory of the legs aud the deviatiou Two t.\·pes of dist.urbances act. upou t.he lIIicrorohot.:
4.2 Description of the system
• a systematic or intrinsic error that leads t.o a ('oust.ant. deviation. It is due ou ouc hami to a dilTerence in t.he manufact.ure of t.he t.hree legs (t.he surface of the electrode or t.he length of t.he legs could be different) ami 011 the other haud to an inevitahle different. posit.iouing of
The goal of this work is to design a fault identification process for the deviat.ion of the microrobot. during a motion . This process must be incorporated into the normal control loop. One approach of a fault dct.ectioll process is a Illodel-based approach (Patton 1994) in which a 654
residual signal is h.uilt up having a scnsitidt.y t.o a 'he block diagram of the general struct.ure fall It.. 1 appears in Fig. 9.
Fault decision logic "t''residual k\ ", , -- - - ,
Fig. 10. Generation of the resit.lual for the deviation analysis
Residual generation
4.3 Deviation Analysis faults
Input
System
The deviation analysis process must ue able to distinguish the systematic errors from the uncert.ain disturbances. One way to do this is to integrate these errors in the microrobot model. As already mentioned the model complexity is too high to be calculated easily. Another way is to realize an on-line learning-and-adaptation approach usiug a neural network that can learn the most coutrol problems aud compensate the systematic disturbance. The input parameters of the neural network are the calculated trajectory, the actual control paramcters from the controller aud the actual positiou of the microrobot. Another possibility is the use of a fuzzy-logic. In this case, the fuzzy-controller which receives the difference between the calculated aud t.he real position ac; input parameter, acts directly upon the controller. The rule base of the fuzzy coutroller contains the ap7'io7'i kuowledge about. the behaviour of t.he microrobot.
Output
fi!!;. 9. Geucral st.ructure of a model-based fault diagnosis
fi!!; . 10 illustrates the case of t.he lllicrorobot syst.em t.hat can Le described wit.h the foIIowillg st.ate equations:
;Ck+1
= I(Xk, Uk, Iu)
Yk+l
= g(;r~,)
At the moment the deviat.ion a.nalysis uses the residual that coutains the iuforl11ation about the position of each leg as well as the dynamic state of the microrobot. The speed of the legs (see Fig. 11) is compared with the input speeds (frequency used for the leg motion). A too important disparity between these two values could indicate a perturbation with a faulty leg or with the part of the surface the leg moves 011.
:r~. represents t.he state vector at. the k-th sampling instaut ali(I is defilled by the co-ordinates of t.he Ipgs of the microrobot amI the angle orientatiou. 111: iu the input vector defined Ly the parameters gi\'en to the systel11 control: the speed and t.he direction of the mot.ion aud this for each leg. I.. are Ill(' s.\·st,Plllatic disturbances and III are the Iluccrtaiu distmiJances. The gloLal seusor (CCD camera) lllPasures the state YI, of the microrobot. wit.h the help of a calibratiou met.hod (fuuct.iou fJ)wich gin'S t.he relationships Let.weell image coordinates and \vorld coordinates. The input parameter 1(1 of t.he systcm is the position of the lIlicrorobot. The llIathematicalmodel of the lllicrorobot. t.
5. CONCLUSIONS AND FUTURE WORKS This paper presented the positioning fault detection of a microrobot in a micromanipulation station. The automation of this st.ation beiug the main goal of the project, several sensors system are used and a fault. diaguosis is ueeded to locat.e different kinds of faults . A first approach \vas the fault occurring during the positioning of a microrobot which is very sensit.ive to the surface it moves OIl. Future work deals with a better understanding of the rouot motion (improvement of the robot lIlodel) and the implementation of the mcthods for the compensatiou of the systematic 655
t >
Fischer, T ., K. Sauta and S. Fatikow (1996). System and powerful cumputer system for COli trolling a microrobot-based micromanipulation station. In: Mic1'OmechaTlics Enrollc, Bar·celona. pp. 283- 286. Magnussen, B. , S. FatikO\v and U. Rembold (1995). Actuation in mic1'Osystems: Problem field overview and practical example of the piezoelectric robot for handling of lIlicroobjects. In: Pmc. ETFA '95, Emc7ging Tcclmologics and FactoT'Y A utoTT!ation, Paris. Vo!. 3. pp. 21- 27. ]'Vlunassypov, R., B. Grossmaull, B. Magnussen and S. Fatikow (1996) . Development and control of piezoelectric actuators for a mobile micromanipulation system. In: Actuator 96 Int. ConJ. on News Actnactor's, Brcmen. pp. 213216. Patton, Ron .1. (1994) . Robust model-based fault diagnosis: the state of the art. In: Fault dctcction, supervision and .safcty for tcchnical pmcesscs, IFAC Symposinm. pp. 1-24. Santa, K., I3. Magnusseu ami S. Fatikow (1996). Miniroboter fiir prazisionsarbeit. Iu: Fcinwcrktcchnik, Mik7'Otcchnik, Mik1'Oelckt1'Ouik. Vo!. 9. pp. 632-634.
Leg 1
~.~ ( ~ 0.51 1
ii '
c--~~-------
s
:1/- ---
"iO
Time (5)
' 'is " '18.9
~~2~"_"_
: c __-
00
5
'16 -
'l
IS
'18.9
Time (5)
Fig. 11. Evolution of the yelocity of each leg dmiug it displacement. dn·iat.ion (neuraluetwork aud fuzzy cont.rul) . The next. step could be tu take int.o accuunt other s('nsors slIch as the loca.l sensor. l\-Iureover se\'(~ral llIicroroLots must. be used toget.her. In t.his case, tlw importance of the fault detection increases, for exalllple to avoid collisions between mic1'Orohots (\)1(1 t.o guarantee a fault-free manipulatiun p1'on'ss.
6. ACKNOWLEDGEMENTS This res(~arch work was performed at the IlIst.itute for n('a.I-Tillle Computer Systems ami Robot.ics, Prof. Dr.-lng. U. Relllbold, Prof. Dr.-lug. H. \V(il'll alld Prof. Dr.-lug. R Dilllllanll, Depart.mcllt of Compllt,pr Science, University uf KarlsrnIH> , GerIU:1I1.\:. The research is fOllnded hy tllP. EC program "HCl\I" , cont.ract IIIlmber CHRXCT940576.
7. REFERENCES Fatikow, S. (1995) . l\Iikrowbot.ik. Ill: 1'alj1L7l.slmnd des 2. W 07'ksh(1) M ethode7l.- 111/,(1 Wer·kzC11.grntwicklnng fur den Mikt·osyslernencntuI1L7j. Karslrulte. pp. 8- 18. Fatikow, S. and U. Rembold (1996). An automat.ed mic1'Orobot-based deskt.op st.at.ion for lIIicro assembly and handliug of lIIicroouj('ct.s. Ill : P7'Oc. ETFA '96, Emrr:ging Technologics /Lnd Fact07'y A uto7llation. Kana i, Ha waii. 656