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Modeling, Identification and Control, Vol. 33, No. 3, 2012, pp. 111–122, ISSN 1890–1328 Multiobjective Optimum Design of a 3-R RR Spherical Parallel Manipulator with Kinematic and Dynamic Dexterities Guanglei Wu 1 1 Department of Mechanical and Manufacturing Engineering, Aalborg University, 9220 Aalborg, Denmark. E-mail: [email protected] Abstract This paper deals with the kinematic synthesis problem of a 3-R RR spherical parallel manipulator, based on the evaluation criteria of the kinematic, kinetostatic and dynamic performances of the manipulator. A multiobjective optimization problem is formulated to optimize the structural and geometric parameters of the spherical parallel manipulator. The proposed approach is illustrated with the optimum design of a special spherical parallel manipulator with unlimited rolling motion. The corresponding optimization problem aims to maximize the kinematic and dynamic dexterities over its regular shaped workspace. Keywords: Spherical parallel manipulator, multiobjective optimization, Cartesian stiffness matrix, dex- terity, Generalized Inertia Ellipsoid 1 Introduction A three Degrees of Freedom (3-DOF) spherical paral- lel manipulator (SPM) is generally composed of two pyramid-shaped platforms, namely, a mobile platform (MP) and a fixed base that are connected together by three identical legs, each one consisting of two curved links and three revolute joints. The axes of all joints intersect at a common point, namely, the center of ro- tation. Such a spherical parallel manipulator provides a three degrees of freedom rotational motion. Most of the SPMs find their applications as orienting de- vices, such as camera orienting and medical instrument alignment (Gosselin and Hamel, 1994; Li and Payan- deh, 2002; Cavallo and Michelini, 2004; Chaker et al., 2012). Besides, they can also be used to develop ac- tive spherical manipulators, i.e., wrist joint (Asada and Granito, 1985). In designing parallel manipulators, a fundamental problem is that their performance heavily depends on their geometry (Hay and Snyman, 2004) and the mu- tual dependency of the performance measures. The manipulator performance depends on its dimensions while the mutual dependency among the performances is related to manipulator applications (Merlet, 2006b). The evaluation criteria for design optimization can be classified into two groups: one relates to the kinematic performance of the manipulator while the other relates to the kinetostatic/dynamic performance of the ma- nipulator (Caro et al., 2011). In the kinematic con- siderations, a common concern is the workspace (Mer- let, 2006a; Kong and Gosselin, 2004; Liu et al., 2000; Bonev and Gosselin, 2006). The size and shape of the workspace are of primary importance. Workspace based design optimization can usually be solved with two different formulations, the first formulation aim- ing to design a manipulator whose workspace contains a prescribed workspace (Hay and Snyman, 2004) and the second approach being to design a manipulator whose workspace is as large as possible (Lou et al., 2005). In Ref. (Bai, 2010), the SPM dexterity was op- timized within a prescribed workspace by identifying doi:10.4173/2012.3.3 c 2012 Norwegian Society of Automatic Control
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Modeling,IdenticationandControl,Vol. 33,No. 3,2012,pp. 111122,ISSN18901328MultiobjectiveOptimumDesignofa3-RRRSpherical Parallel ManipulatorwithKinematicandDynamicDexteritiesGuangleiWu11DepartmentofMechanical andManufacturingEngineering,AalborgUniversity,9220Aalborg,Denmark.E-mail: gwu@m-tech.aau.dkAbstractThispaperdealswiththekinematicsynthesisproblemofa3-RRRsphericalparallelmanipulator,basedon the evaluation criteria of the kinematic,kinetostatic and dynamic performances of the manipulator. Amultiobjectiveoptimizationproblemisformulatedtooptimizethestructural andgeometricparametersof thespherical parallel manipulator. Theproposedapproachisillustratedwiththeoptimumdesignofaspecial spherical parallel manipulatorwithunlimitedrollingmotion. Thecorrespondingoptimizationproblemaimstomaximizethekinematicanddynamicdexteritiesoveritsregularshapedworkspace.Keywords: Sphericalparallelmanipulator, multiobjectiveoptimization, Cartesianstinessmatrix, dex-terity,GeneralizedInertiaEllipsoid1 IntroductionAthreeDegreesofFreedom(3-DOF)spherical paral-lel manipulator (SPM) is generallycomposedof twopyramid-shapedplatforms, namely, amobileplatform(MP)andaxedbasethatareconnectedtogetherbythreeidentical legs, eachoneconsistingoftwocurvedlinksandthreerevolutejoints. Theaxesof all jointsintersectatacommonpoint,namely,thecenterofro-tation. Suchasphericalparallelmanipulatorprovidesathree degrees of freedomrotational motion. Mostof the SPMs ndtheir applications as orientingde-vices, such as camera orienting and medical instrumentalignment(GosselinandHamel, 1994; Li andPayan-deh, 2002; CavalloandMichelini, 2004; Chakeretal.,2012). Besides, theycanalsobeusedtodevelopac-tive spherical manipulators, i.e., wrist joint (Asada andGranito,1985).Indesigning parallel manipulators, a fundamentalproblemisthattheirperformanceheavilydependsontheirgeometry(HayandSnyman, 2004)andthemu-tual dependencyof the performance measures. Themanipulator performance depends onits dimensionswhile the mutual dependency among the performancesis related to manipulator applications (Merlet, 2006b).Theevaluationcriteriafordesignoptimizationcanbeclassied into two groups: one relates to the kinematicperformance of the manipulator while the other relatestothe kinetostatic/dynamic performance of the ma-nipulator (Caroet al., 2011). Inthekinematiccon-siderations,acommonconcernistheworkspace(Mer-let, 2006a; KongandGosselin, 2004; Liuetal., 2000;Bonev andGosselin, 2006). The size andshape oftheworkspaceareofprimaryimportance. Workspacebaseddesignoptimizationcanusuallybesolvedwithtwodierent formulations, therst formulationaim-ingtodesignamanipulatorwhoseworkspacecontainsaprescribedworkspace(HayandSnyman, 2004)andthe secondapproachbeing to designa manipulatorwhose workspace is as large as possible (Louet al.,2005). InRef.(Bai,2010),theSPMdexteritywasop-timizedwithinaprescribedworkspacebyidentifyingdoi:10.4173/2012.3.3 c2012NorwegianSocietyofAutomaticControlModeling,IdenticationandControl(a) (b)Figure1:3-RRRunlimited-rollSPM:(a)CADmodel,(b)applicationassphericallyactuatedjoint.thedesignspace. Itisknownfrom(GosselinandAn-geles, 1989)thattheorientationworkspaceof aSPMisamaximumwhenthegeometricanglesofthelinksareequalto90o. However,maximizingtheworkspacemayleadtoapoordesignwithregardtothemanip-ulator dexterityandmanipulability(Stamper et al.,1997;DurandandReboulet,1997). Thisproblemcanbesolvedbyproperlydeningtheconstraintsondex-terity(Merlet, 2006a; Huang et al., 2003). For theoptimumdesignof SPMs, anumber of works focus-ingonthekinematicperformance, mainlythedexter-ityandworkspace, havebeenreported, whereas, thekinetostatic/dynamic aspects receive relatively less at-tention. Ingeneral,thedesignprocesssimultaneouslydealswiththetwopreviouslymentionedgroups,bothof whichinclude anumber of performance measuresthat essentially vary throughout the workspace. On thekinetostaticaspect,theSPMstinessisanimportantconsideration (Liu et al., 2000) to characterize its elas-tostaticperformance. Whentheyareusedtodevelopsphericallyactuatedjoint, not onlythe MPangulardisplacement but also the translational displacement ofthe rotation center should be evaluated from the Carte-sianstinessmatrixofthemanipulatorandshouldbeminimized. Moreover, the dynamic performance of themanipulatorshouldbeashighaspossible.Amongtheevaluationcriteriaforoptimumgeomet-ricparametersdesign,anecientapproachistosolvea multiobjective optimization problem, which takes allormostoftheevaluationcriteriaintoaccount. Astheobjective functions are usually conicting, no single so-lutioncanbeachievedinthisprocess. Thesolutionsof suchaproblemarenon-dominatedsolutions, alsocalledPareto-optimal solutions. Somemultiobjectiveoptimizationproblemsofparallelmanipulators(PMs)have been reported in the last few years. Hao and Mer-letproposedamethoddierentfromtheclassical ap-proaches to obtain all the possible design solutions thatsatisfyasetofcompulsorydesignrequirements,wherethe designspace is identiedviathe interval analy-sisbasedapproach(HaoandMerlet,2005). Ceccarellietal. focusedontheworkspace, singularityandsti-ness properties to formulate a multi-criterion optimumdesignprocedureforbothparallel andserial manipu-lators(Ceccarelli etal., 2005). StockandMillerfor-mulatedaweightedsummulti-criterionoptimizationproblem with manipulability and workspace as two ob-jectivefunctions(StockandMiller, 2003). KretandHesselbach formulated a multi-criterion elastodynamicoptimization problemfor parallel mechanisms whileconsideringworkspace, velocitytransmission, inertia,stiness and the rst natural frequency as optimizationobjectives(KretandHesselbach,2005). Altuzarraetal. dealtwiththemultiobjectiveoptimumdesignofaparallelSchoniesmotiongenerator,inwhichthema-nipulator workspace volume and dexterity were consid-eredasobjectivefunctions(Altuzarraetal.,2009).Inthis work, amultiobjective designoptimizationproblemisformulated. Thedesignoptimizationprob-lemof the3-DOFspherical parallel manipulatorcon-siders the kinematic performance, the accuracy and thedynamic dexterity of the mechanism under design. Theperformances of the mechanism are also optimized overaregular shapedworkspace. Themultiobjectivede-112G.Wu,Multiobjectiveoptimizationofsphericalparallelmanipulator(a) (b)Figure2:ArchitectureofageneralSPM:(a)overview,(b)parameterizationoftheithleg.signoptimizationproblemisillustratedwitha3-RRRSPMshowninFigure1, whichcanreplacetheserialchains basedwrist mechanisms. Thenon-dominatedsolutions, alsocalledPareto-optimal solutions, of themultiobjective optimization problem are obtained withageneticalgorithm.2 ManipulatorArchitectureThe spherical parallel manipulator under studyis anovel robotic wrist with an unlimited roll motion (Bai,2010; Bai et al., 2009), whichonlyconsists of threecurved links connected to a mobile platform (MP). Themobile platform is supposed to be quite stier than thelinks, whichisconsideredasarigidbody. Thethreelinks are drivenbythree actuators movingindepen-dentlyonacircularrailofmodelHCR150fromTHKviapinionandgear-ringtransmissions. Thankstothecircular guide, the overall stiness of the mechanism isincreased. Moreover, suchadesignenablestheSPMto generate an unlimited rolling motion,in addition tolimitedpitchandyawrotations.AgeneralsphericalparallelmanipulatorisshowninFigure2(a)(Liuetal., 2000). Figure2(b)representsthe parameters associated with the ith leg of the SPM,i=1,2,3. TheSPMiscomposedof threelegsthatconnectthemobile-platformtothebase. Eachlegiscomposed of three revolute joints. The axes of the revo-lutejointsintersectandtheirunitvectorsaredenotedbyui, wiandvi, i =1,2,3. Thearcanglesof thethreeproximalcurvedlinksarethesameandequalto1. Likewise,thearcanglesofthethreedistalcurvedlinksarethesameandequal to2. Theradii of thelink midcurves are the same and equal to R. Geometricangles and dene the geometry of the two pyrami-dalbaseandmobileplatforms. ThepresentedSPMinFigure1(a)isaspecialcasewith= 0. TheoriginOof the reference coordinate system Fais located at thecenterofrotation.3 KinematicandKinetostaticModelingoftheSPMThe kinematics of the SPMs has been well docu-mented(GosselinandAngeles,1989),whichisnotre-peatedindetailhere. Hereafter,theorientationofthemobileplatformisdescribedbytheorientationrepre-sentationof azimuth-tilt-torsion( ) (Bonev,2008),forwhichtherotationmatrixisexpressedasQ =__ccc( ) + ss( ) ccs( ) sc( ) csscc( ) cs( ) scs( ) + cc( ) sssc( ) ss( ) c__(1)113Modeling,IdenticationandControlwhere (,], [0,), (,],ands() =sin(),c() = cos().Under the prescribed coordinate system, unit vectoruiisexpressedinthebaseframe Fabelow:ui=_sin i sin cos i sin cos T(2)wherei= 2(i 1)/3,i = 1,2,3.Unit vector wi of the intermediate revolute joint axisintheithlegisexpressedin Faas:wi=__sisc1 + (cisisicci)s1cisc1 + (sisi + cicci)s1cc1 + scis1__(3)Theunitvectorviof thelastrevolutejointaxisintheithleg,isafunctionofthemobile-platformorien-tation,namely,vi= Qvi(4)where vicorresponds to the unit vector of the last rev-olute joint axis in the ith leg when the mobile platformisinitshomeconguration:vi=_sin i sin cos i sin cos T(5)3.1 KinematicJacobianmatrixLet denote the angular velocity of the mobile-platform, thescrewsvelocityequationviatheithlegcanbestatedas$=_0_ =i$iA +i$iB +i$iC(6)with the screws for the revolute joints at points Ai, BiandCiexpressedas$iA=_ui0_,$iB=_wi0_,$iC=_vi0_Since the axes of the two passive revolute joints in eachleg lie in the plane BiOCi, the following screw is recip-rocaltoalltherevolutejointscrewsoftheithleganddoesnotlieinitsconstraintwrenchsystem:$ir=_0wivi_(7)Applyingtheorthogonal product () (Tsai, 1998) tobothsidesofEqn.(6)yields$ir $= (wivi)T= (uiwi) vi i(8)As aconsequence, the expressionmappingfromthemobile platform twist to the input angular velocities isstatedas:A= B (9)withA =_a1a2a3,ai= wivi(10a)B = diag_b1b2b3,bi= (uiwi) vi(10b)where=_123T. MatricesAandBaretheforwardandinverseJacobianmatricesofthemanipu-lator, respectively. If Bisnonsingular, thekinematicJacobianmatrixJisobtainedasJ = B1A (11)3.2 CartesianstinessmatrixThestinessmodel oftheSPMunderstudyisestab-lishedwithvirtualspringapproach(Pashkevichetal.,2009), byconsideringtheactuationstiness, linkde-formationandtheinuenceofthepassivejoints. TheexiblemodeloftheithlegisrepresentedinFigure3.Figure3(b) illustrates thelinkdeections andvaria-tionsinpassiverevolutejointangles.Letthecenterof rotationbethereferencepointofthe mobile platform. AnalogtoEqn. (6), the smalldisplacementscrewofthemobile-platformcanbeex-pressedas:$iO=_p_ = i$iA + i$iB + i$iC(12)wherep=[x,y,z]Tislineardisplacementofthe rotationcenter and=[x,y,z]Tisthe MP orientation error. Note that this equation onlyincludesthejointvariations,whilefortherealmanip-ulator,linkdeectionsshouldbeconsideredaswell.Thescrewsassociatedwiththelinkdeectionsareformulatedasfollows:$iu1=_ririC ri_,$iu2=$iC,$iu3=_niriC ni_(13)$iu4=_0ri_,$iu5=_0vi_,$iu6=_0ni_where ni=wi viis the normal vectors of planeBiOCi,ri= wi ni,andriCisthepositionvectorofpointCifromO. Thedirectionsofthevectorsriandniareidenticaltoui4andui6,respectively.Byconsideringthe linkdeections ui1...ui6andvariations inpassive joint angles andaddingall thedeectionfreedomstoEqn. (12), themobileplatformdeectionintheithlegisstatedas$iO=i$iA + i$iB + i$iC+ ui1$iu1 + ui2$iu2+ ui3$iu3 + ui4$iu4 + ui5$iu5 + ui6$iu6(14)Thepreviousequationcanbewritteninacompactformbyseparatingthetermsrelatedtothevariations114G.Wu,Multiobjectiveoptimizationofsphericalparallelmanipulator(a)(b)Figure3:Flexible model of a single leg: (a) virtualspring model, where Acstands for the actua-tor, R for revolute joints and MP for the mo-bileplatform, (b) linkdeections andjointvariationsintheithleg.inthepassiverevolutejointanglesandthoserelatedtotheactuatorandlinkdeections,namely,$iO= Jiui +Jiqqi(15)withJi=_$iA$iu1$iu2$iu3$iu4$iu5$iu6_(16a)Jiq=_$iB$iC_(16b)ui=_iui1ui2ui3ui4ui5ui6T(16c)qi=_iiT(16d)Let the external wrench applied to the end of the ithleg be denoted by fi, the constitutive law of the ith legcanbeexpressedasfi=_KrrKrtKTrtKtt_i_p_ fi= Ki$iO(17)Ontheotherhand, thewrenchappliedtothearticu-lated joints in the ith leg being denoted by a vector i,theequilibriumconditionforthesystemiswrittenas,JiTfi= i, JiTqfi= 0, ui= Ki1i(18)CombiningEqns.(15), (17)and(18), thekinetostaticmodel of the ith leg can be reduced to a system of twomatrixequations,namely,_ SiJiqJiqT022_ _fiqi_ =_$iO021_(19)wherethesub-matrixSi=JiKi1JiTdescribes thespringcompliance relative tothe center of rotation,andthesub-matrixJiqtakesintoaccountthepassivejointinuenceonthemobileplatformmotions.Ki1isa7 7matrix,describingthecomplianceofthevirtualspringsandtakingtheform:Ki1=_Ki1act016061Ki1L_(20)where Kiact corresponds to the stiness of the ith actua-tor. KiL of size 66 is the stiness matrix of the curvedlinkintheithleg,whichiscalculatedbymeansoftheEuler-Bernoullistinessmodelofacantilever. InFig-ure3(b), u1, u2andu3showthethreemomentdirections while u4, u5andu6showthe threeforce directions, thus, using Castiglianos theorem (Hi-bbeler, 1997), the compliance matrix of the curved linktakestheform:Ki1L=__C11C120 0 0 C16C12C220 0 0 C260 0 C33C34C3500 0 C34C44C4500 0 C35C45C550C16C260 0 0 C66__(21)where the corresponding elements are given in Ap-pendixA.ThematrixJiof size6 7istheJacobianmatrixrelatedtothevirtualspringsandJiqof6 2,theonerelatedtorevolutejoints intheithleg. TheCarte-sianstinessmatrixKioftheithlegisobtainedfromEqn.(19),fi= Ki$iO(22)where Kiis a 66 sub-matrix, which is extracted fromtheinverseofthe8 8matrixontheleft-handsideofEqn.(19). Fromf=

3i=1fi,$O= $iOandf= K$O,the Cartesian stiness matrix K of the system is foundbysimpleaddition,namely,K =3

i=1Ki(23)115Modeling,IdenticationandControl3.3 MassmatrixThemassinmotionof themechanisminuencesthedynamic performance, such as inertia, acceleration,etc.,hence,formulatingthemassmatrixisoneimpor-tantprocedureinthedynamicanalysis. Massmatrixis the function of manipulator dimensions and materialproperties,i.e.,linklengths,cross-sectionalarea,massdensity. Generally, the manipulator mass matrix (iner-tiamatrix)canbeobtainedonthebasisofitskineticenergy. The total kinetic energy Tincludes the energyTpof themobileplatform, Tlof thecurvedlinksandTsoftheslideunits: ThekineticenergyofthemobileplatformisTp=12mpvTpvp +12TIp (24)withvp= Rcos p ,Ip= diag [IxxIyyIzz] (25)wherempisthemassofthemobile-platformandIxx, Iyy, Izzare the mass moments of inertia of themobile-platform about x-,y-,z-axes,respectively. ThekineticenergyofthecurvedlinksisTl=123

i=1_mlviTlvil+Il2i_(26)withvil=12R_iwiui +vi_(27a)Il=12mlR2_1 sin 2 cos 22_(27b)i= (uivi) (uiwi) vi= ji (27c)wheremlisthelinkmassandIlisitsmassmo-mentofinertiaaboutwi. ThekineticenergyoftheslideunitsisTs=12_Ign2g +msR2s_T (28)wheremsisthemassof theslideunitandRsisthedistancefromitsmasscentertoz-axis. Igisthemassmomentof inertiaof thepinionandngisthegearratio.Consequently, theSPMkineticenergycanbewritteninthefollowingformT= Tp +Tl +Ts=12TM (29)Figure4:TherepresentationoftheregularworkspacefortheSPMwithapointingcone.withthemassmatrixMofthesystemisexpressedasM =_msR2s +Ign2g +14mlR2sin21_13+JT_Ip +mpR2cos2[p]T[p]+14mlR23

i=1[vi]T[vi] +Il3

i=1jijTi_J (30)where [] stands for the skew-symmetric matrix whoseelementsarefromthecorrespondingvectorand13istheIdentitymatrix.4 DesignOptimizationoftheSpherical Parallel ManipulatorTheinversekinematicproblemof theSPMcanhaveuptoeight solutions, i.e., the SPMcanhave uptoeightworkingmodes. Here, thediagonal termsbioftheinverseJacobianmatrixBaresupposedtobeallnegative for the SPM to stay in a given working mode.Intheoptimizationprocedure,criteriainvolvingkine-matic and kinetostatic/dynamic performances are con-sidered to determine the mechanism conguration andthedimensionandmasspropertiesofthelinks. More-over, the performances are evaluatedover a regularshapedworkspace free of singularity, whichis speci-edasaminimumpointingconeof 90oopeningwith116G.Wu,MultiobjectiveoptimizationofsphericalparallelmanipulatorFigure5:Designvariablesofthe3-RRRSPM.360ofullrotation,i.e., 45oand (180o,180o],seeFigure4.4.1 DesignvariablesVariables 1, 2, and arepart of thegeometricparametersof a3-RRRSPMand=0forthema-nipulatorunderstudy. Moreover, theradiusRofthelinkmidcurveisanotherdesignvariableandthecrosssectionofthelinksissupposedtobeasquareofsidelengtha. ThesevariablesareshowninFigure5. Asaconsequence,the design variable vector is expressed asfollows:x = [1,2,,a,R] (31)4.2 ObjectivefunctionsThekinematicperformanceis oneof themajor con-cernsinthemanipulatordesign, of whichacriterionis the evaluationof the dexterityof SPMs. Acom-monlyusedcriteriontoevaluate this kinematic per-formanceistheglobalconditioningindex(GCI)(Gos-selinandAngeles,1991),whichdescribestheisotropyof the kinematic performance. The GCI is dened overaworkspaceasGCI=_1(J)dW_ dW(32)where(J)istheconditionnumberof thekinematicJacobian matrix (11). In practice, the GCI of a roboticmanipulatoriscalculatedthroughadiscreteapproachasGCI=1nn

i=11i(J)(33)where n is the number of the discrete workspace points.As a result, the rst objective function of the optimiza-tionproblemiswrittenas:f1(x) = GCI max (34)Referringtothekinematicdexterity, animportantcriteriontoevaluatethedynamicperformanceisdy-namic dexterity, whichis made onthe basis of theconcept of Generalized Inertia Ellipsoid (GIE) (Asada,1983). Inordertoenhancethedynamicperformanceand to make acceleration isotropic, the mass ma-trix(30) shouldbeoptimizedtoobtainabetter dy-namicdexterity. SimilartoGCI,aglobaldynamicin-dex(GDI)isusedtoevaluatethedynamicdexterity,namely,GDI=1nn

i=11i(M)(35)wherei(M)istheconditionnumberofthemassma-trixoftheithworkspacepoint. Thus, thesecondob-jectivefunctionoftheoptimizationproblemiswrittenas:f2(x) = GDI max (36)4.3 OptimizationconstraintsInthis section, thekinematicconstraints, condition-ingof thekinematicJacobianmatrixandaccuraciesduetotheelasticdeformationareconsidered. Con-straining the conditioning of the Jacobian matrix aimstoguaranteedexterous workspacefreeof singularity,whereaslimitsonaccuracyconsiderationensuresthatthemechanismissucientlysti.4.3.1 KinematicconstraintsAccording to the determination of design space re-portedin(Bai, 2010), the bounds of the parameter1, 2andsubjecttotheprescribedworkspacearestatedas:45o 90o, 45o 1,2 135o(37)Thesequenceoftherst,secondandthirdslideunitsappearing on the circular guide counterclockwise isconstant. Inorder to avoidcollision,the angles ijbe-tweentheprojectionsofvectorswiandwjinthexyquadrant, i,j =1,2,3, i =j, asshowninFigure6,havetheminimumvalue, say10o. Toavoidcollision117Modeling,IdenticationandControlFigure6:Slideunitcongurationofthe3-DOFSPM.andmakethemechanismcompact, thefollowingcon-straintsshouldbesatised:12,23,31 = 10o(38)R0= 0.120 m Rsin 1 Rs= 0.200 mMoreover, the SPM should not reach any singularityinitsorientationworkspace. Therefore, thefollowingconditionsshouldbesatised.det(A) , bi= (uiwi) vi (39)whereAistheforwardJacobianmatrixofthemanip-ulator denedinEqn. (9) and >0is apreviouslyspeciedtolerancesetto0.001.4.3.2 ConditioningnumberofthekinematicJacobianmatrixMaximizing the GCI and constraining the kine-maticJacobianmatrixcannotpreventtheprescribedworkspace away fromill-conditioned congurations.Forthedesignoptimizationinordertoachieveadex-terousworkspace, theminimumof theinversecondi-tion number of the kinematic Jacobian matrix 1(J),basedon2-norm, shouldbehigherthanaprescribedvaluethroughouttheworkspace,say0.1,namely,min(1(J)) 0.1 (40)4.3.3 AccuracyconstraintsThe accuracy constraints of the optimization prob-lemfor the SPMare related to the dimensions ofTable1:The lower andupper bounds of the designvariablesx.1 [deg] 2 [deg] [deg] a [m] R[m]xlb45 45 45 0.005 0.120xub135 135 90 0.030 0.300the curvedlinkandthe maximumpositional deec-tionof the rotationcenter andangular deectionofthe moving-platform subject to a given wrench appliedonthe latter. The control loopstiness is Kiact=106Nm/rad. Letthestaticwrenchcapabilitybespec-iedas the eight possible combinations of momentsm=[10, 10, 10] Nm, whiletheallowablemaxi-mum positional and rotational errors for the workspacepoints are 1 mmand 2o=0.0349 rad, respectively,thus,theaccuracyconstraintscanbewrittenas:pn=_x2n + y2n + z2n p(41)n=_2x, n + 2y, n + 2z, n rwherethelinearandangulardisplacementsarecom-putedfrom$O=K1f withtheCartesianstinessmatrix(23)andp= 1 mm,r= 0.0349 rad.4.4 FormulationofthemultiobjectiveoptimizationproblemMathematically, themulti-objectivedesignoptimiza-tion problem for the spherical parallel manipulator canbeformulatedas:maximize f1(x) = GCI (42)maximize f2(x) = GDIover x = [1,2,,a,R]subject to g1: 45og2: R0 Rsin 1 Rsg3: 12,23,31 = 10og4: det(A) , (uiwi) vi g5: min(1(J)) 0.1g6:_x2n + y2n + z2n pg7:_2x, n + 2y, n + 2z, n rxlb x xubi = 1,2,3wherexlbandxub,respectively,arethelowerandup-perboundsofthevariablesxgivenbyTable1.118G.Wu,MultiobjectiveoptimizationofsphericalparallelmanipulatorTable2:AlgorithmparametersoftheimplementedNSGA-IIPopulation Generation Directionalcrossover Crossover Mutation Distributionsize probability probability probability index40 200 0.5 0.9 0.1 20Table3:ThreePareto-optimalsolutionsDesign Variables ObjectivesID 1 [deg] 2 [deg] [deg] a [m] R[m] GCI GDII 56.2 81.0 89.8 0.0128 0.1445 0.366 0.711II 51.6 84.3 89.9 0.0133 0.1533 0.453 0.665III 47.2 90.8 89.2 0.0127 0.1641 0.536 0.6254.5 Pareto-optimal solutionsFor the proposed SPM, the actuation transmissionmechanismis a combination of actuator of modelRE35 GB and gearhead of model GP42 C fromMaxon(Maxon, 2012) andaset of gear ring-pinionwithrationg= 8. Moreover,thecomponentsaresup-posed to be made of steel, thus, E= 210 Gpa, = 0.3.Moreover, the moving platform is supposed to be a reg-ulartriangle, thus, theMPandlinkmassesaregivenbymp=334hR2sin2,ml= a2R2(43)whereis themass densityandh=0.006 mis thethicknessofthemovingplatform. Thetotal massmsofeachslideunit, includingthemassoftheactuator,gearhead, pinion and the manufactured components, isequaltoms= 2.1 kg.Thepreviousformulatedoptimizationproblem(42)is solved by the genetic algorithm NSGA-II (Deb et al.,2002)withMatlab,ofwhichthealgorithmparametersaregiveninTable2.The Pareto front of the formulated optimizationproblemfortheSPMisshowninFigure7andthreeoptimal solutions, i.e., two extreme and one intermedi-ate,arelistedinTable3.Figure8illustratesthevariationaltrendsaswellastheinter-dependencybetweentheobjectivefunctionsand design variables by means of a scatter matrix. Thelowertriangularpartofthematrixrepresentsthecor-relationcoecientswhereastheupperoneshowsthecorresponding scatter plots. The diagonal elementsrepresent theprobabilitydensitycharts of eachvari-able. Thecorrelationcoecientsvaryfrom 1to1.Twovariablesarestronglydependentwhentheircor-relation coecient is close to 1 or 1 and independentwhenthelatterisnull. Figure8shows: both objectives functions GCI and GDI are0.35 0.4 0.45 0.5 0.550.620.630.640.650.660.670.680.690.70.710.72ID IID IIID IIIKinematic dexterityDynamic dexterityFigure7:TheParetofrontofthemultiobjectiveopti-mizationproblemfortheSPM.stronglydependentastheircorrelationcoecientisequalto 0.975; both objectives functions GCI and GDI arestronglydependent onall designvariables as allof the corresponding correlation coecients aregreaterthan0.6; GCIisslightlymoredependentthanGDIofthedesignvariablesasall thecorrespondingcorrela-tioncoecientsof formeraregreaterthanthoseoflatter; GDI islessdependentonthedesignvariablesandathantheothervariablesalthoughthetwoformervariablesinuencetheSPMmass, thisisduetothelargeportionoftheslideunitmassinthetotalmechanismmass.119Modeling,IdenticationandControlFigure8:Scattermatrixfortheobjectivefunctionsandthedesignvariables.0.35 0.4 0.45 0.5 0.55406080100Variables [deg]Kinematic dexterityGCI 120.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.7 0.71 0.72406080100Variables [deg]Dynamic dexterityGDI 120.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.7 0.71 0.720.10.120.140.160.18Variables [m]Dynamic dexterityGDI 10*aRFigure9:Design variables as functions of objectives forthePareto-optimalsolutions.Figure9displays thedesignvariables as functionsof the objectives. It is noteworthy that the higherGCI, thelower 1, conversely, thehigher GDI, thehigher1. Thisphenomenonisoppositewithrespecttovariable2. Thedesignvariableconvergesto90oapproximately, which indicates that = 90ois the pre-ferredgeometricparameterfortheSPMunderstudy.The lower link midcurve R and higher a lead to higherGDI. The three sets of of design variables correspond-ingtothethreePareto-optimal solutionsdepictedinTable3areshowninFigure9withsolidmarkers.5 ConclusionsIn this paper, the geometric synthesis of spherical par-allel manipulators is discussed. Amultiobjectivede-signoptimizationproblembasedonthegeneticalgo-rithmwasformulatedinordertodeterminethemech-anismoptimumstructural andgeometricparameters.The objective functions were dened on the basis of thecriteria of bothkinematic andkinetostatic/dynamicperformances. This approachis illustratedwiththeoptimumdesignofanunlimited-rollspherical parallelmanipulator,aimingatmaximizingthekinematicanddynamicdexterities toachieverelativelybetter kine-maticanddynamicperformancessimultaneously. Itisfound that the parameter being equal to 90ois a pre-ferredstructurefortheSPMunderstudy. Finally,thePareto-frontwasobtainedtoshowtheapproximationof theoptimal solutionsbetweenthevarious(antago-nistic)criteria, subjecttothedependencyof theper-formance. Thefutureworkwill aimtomaximizetheorientationworkspaceandoptimizethecross-sectiontypeofthecurvedlinks.ReferencesAltuzarra, O., Salgado, O., Hernandez, A., andAngeles, J. Multiobjective optimum design ofa symmetric parallel schonies-motion generator.120G.Wu,MultiobjectiveoptimizationofsphericalparallelmanipulatorASMEJ. Mechanical Design, 2009. 131(3):031002.doi:10.1115/1.3066659.Asada, H. Ageometrical representationof manipu-lator dynamics andits applicationtoarmdesign.ASME J. 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TheJacobiananalysisofparallel manip-ulatorsusingreciprocal screws. InJ. LenarcicandM. L. Husty, editors, Advances inRobot Kinemat-ics: Analysis andControl, pages 327336. KluwerAcademicPublishers,1998.AppendixAThe elements of the compliance matrix(21) for thecurvedbeamC11=R2_s1GIx+s2EIy_(A-1a)C12=s8R2_1GIx1EIy_(A-1b)C16=R22_s2EIys7GIx_(A-1c)C22=R2_s2GIx+s1EIy_(A-1d)C26=R22_s4GIxs2EIy_(A-1e)C33=R2EIz(A-1f)C34=s5R2EIz(A-1g)C35=s6R2EIz(A-1h)C44=R2A_s1E+s2G_+s3R32EIz(A-1i)C45=s8R2A_ 1E 1G_+s4R32EIz(A-1j)C55=R2A_s1G+s2E_+s2R32EIz(A-1k)C66=R2GA+R32_s3GIx+s2EIy_(A-1l)withs1= 2 + sin 2 cos 2(A-2a)s2= 2sin 2 cos 2(A-2b)s3= 32 + sin 2 cos 2/2 4 sin 2(A-2c)s4= 1 cos 2sin22/2 (A-2d)s5= sin 22(A-2e)s6= cos 21 (A-2f)s7= 2 sin 22sin 2 cos 2(A-2g)s8= sin22(A-2h)whereEistheYoungsmodulusandG = E/2(1 + )istheshearmoduluswiththePoissonsratio. Ix,IyandIzarethemomentsof inertia, respectively. Aistheareaofthecross-section.122


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