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2009 IEEE International Conference on Robotics and Automation Kobe International Conference Center Kobe, Japan, May 12-17, 2009 Modeling and Control of a Pair of Robot Fingers with Saddle Joint under Orderless Actuations Morio Yoshida, Suguru Arimoto, and Kenji Tahara z Saddle Joint O Abstract— A new robot hand dynamics model with rolling constraints and with a saddle joint at one finger is proposed, where two saddle-joint actuations are considered to be orderless. Spinning motion around the opposition axis connecting two center points of each finger-tip contact area with an object is faithfully treated, and a viscosity model for damping rotational motion of the object is proposed. A class of control signals without referring to object kinematics or using external sensing is proposed. Finally, numerical simulation results show the stability of motion of the overall closed-loop dynamics supplied with the proposed control input. y Rolling Contacts I. I NTRODUCTION The whole stimuli to the human brain, which arise from making and using tools by hands, have accelerated the evolutionary speed of the human brain. The primatologist Napier [1] claims that most of important movements of the hands are based upon finger-thumb opposition shown in Fig.1, that has contributed to the progress of humanity. Despite such a profound proposition, there is a dearth of robotic researches paying much attention to consideration of control functions of multi-fingered hands. For the sake of raveling mysteries of the human hand and realizing its dexterous movements, many robotic researchers devote a lot of their elaborate efforts to the research of robot hands [2] [3] [4]. However, most of the researchers were attracted by kinematics and planning of motions realizing force/torque closure for stable grasp by robot fingers in a static sense. On the other hand, rolling geometry between two arbitrarily-shaped objects is rigorously discussed [5] [6]. However, all the researches have remained in a kinematic or semi-dynamic meaning. In the field of multibody dynamics [7], many models with constraints in 3-D space are presented without modeling physically faithful interaction between a robot finger and an object surface through 3-D rolling. An explicit 3-D dynamical pinching model with rolling constraints between a finger end and an object surface has been missing. Around the year of 2000, Arimoto et al. first showed that 2-D object pinching is realized by using a pair of robot fingers with hemispherical ends, succeeding at embedding This work was partially supported by Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research (B) (20360117). M. Yoshida, S. Arimoto, and K. Tahara are with the RIKEN-TRICollaboration Center for Human-Interactive Robot Research, RIKEN, Nagoya, Aichi, 463-0003, Japan [email protected] S. Arimoto is with the Department of Robotics, Ritsumeikan University, Kusatsu, Shiga, 525-8577, Japan [email protected] K. Tahara is with the Organization for the Promotion of Advanced Research, Kyushu University, Fukuoka, 819-0395, Japan [email protected] 978-1-4244-2789-5/09/$25.00 ©2009 IEEE x Fig. 1. Human pinch motion based on fingers-thumb opposition z z O O q21z , x q11 q21x x Saddle Joint y q12 Gravity direction r21z O01 Oc.m. q13 y Z O2 X O1 q22 O02 Y Fig. 2. Two robot fingers with soft tips pinching an object with parallel flat surfaces under gravity z x O' y Fig. 3. Modeling of a saddle joint in human thumb [5] rolling constraints into the overall fingers-object dynamics [8] [9]. The degrees-of-freedom redundancy problem of the overall fingers-object dynamics for desired tasks is overcome by proposing a stability concept called “Stability on a 2499 manifold”. In the year of 2006 [10], modeling of motion of pinching an object was extended from two-dimensional to three-dimensional pinching. In the modeling of pinching it is assumed that spinning motion of the object around the opposition axis connecting two contact points between the left or right finger end and the object surface has ceased and will not arise any more due to dry friction and microdeformations near the two contact points. This assumption leads to a five-variables model of the object dynamics. In the year of 2008 [11] [12] [13], instead of this assumption, the modeling problem was posed as a more faithful model considering that spinning motion of the object is possible to arise but viscosity friction is exerted on x axis in the frame coordinates O − xyz (see Figure 2), which means the overall fingers-object dynamics as a full variables model is derived. Furthermore, in the previous paper [12], two saddle-joint motors of the robot finger are actuated in sequence. However, the saddle joint of the human thumb must be actuated around the two axes respectively without making any order [14] (see Figure 3). In this paper, we propose a saddle joint model with the orderless relation like the human thumb, and a robot hand model with the saddle joint through taking account of rolling constraints that are Pfaffian. A pair of robot fingers with hemispherical tips made from soft material is treated under the gravity effect. Simple control signals based on the opposability without using object kinematics or external sensing are shown, which are the same as the previously-proposed control signals [11] [12] [13]. Finally, for the sake of confirmation of the stability analysis, we carry out numerical simulations based on the proposed model of object-fingers dynamics and control signals. Since the first joint J21 of the robot finger shown in Fig.4 has orderless saddle-joint actuations, the Denavit-Hartenberg Notation is not applied to derive a geometrical relation of robot kinematics. In this section, a kinematic geometry of the robot finger with orderless actuations, the structure of which is similar to a saddle-joint model of the human thumb [14](see Figure 3), is derived. The coordinate system shown Fig.4 is right-handed. The first joint with center O depicted in Fig.3 is a saddle joint exerted by two actuators, one of which rotates around x-axis and another around z- axis, q̇21x denotes the angular velocity around x-axis and q̇21z around z-axis respectively, where q̇ 21 = (q̇21x , 0, q̇21z )T denotes the rotational vector of the first link with the saddle joint in terms of frame coordinates O − xyz (see Figure 4). We set the Cartesian coordinates Oc.m.21 − X21 Y21 Z21 fixed at the first link frame of the robot hand, and denote three orthogonal unit vectors at the first link frame in each corresponding direction X21 ,Y21 , and Z21 by rX21 = (rXx21 , rXy21 , rXz21 )T , rY 21 = (rY x21 , rY y21 , rY z21 )T , and r Z21 = (rZx21 , rZy21 , rZz21 )T as shown in Fig.4. We derive the mass center Oc.m.21 of the right robot finger by xm21 = (xm21 , ym21 , zm21 )T = s21 r Y 21 + (L, 0, 0)T based s21 l 21 s22 l 22 rZ22 l22-s22 rY22 Y22 Z 22(=Z21) Z21 y q22 rX22 O02 z x . q21x rX21 rY21 Y21 Oc.m.22 . q21z Z 21 rZ21 l21-s21 X 21 Oc.m.21 J22 z . q22z x . q21x X 22 . q22y y Fig. 4. Modeling of the right robot finger with a saddle joint which has orderless actuations on the frame coordinates O − xyz (see Figure 2). It is well known that the 3 × 3 rotation matrix R21 (t) = (rX21 , rY 21 , rZ21 ) ∈ SO(3) (1) which is subject to the first-order differential equation representing infinitesimal rotation as follows: d R21 (t) = R21 (t)Ω21 (t) dt where II. G EOMETRY OF ROBOT F INGER WITH O RDERLESS ACTUATIONS O' J21 ⎛ 0 Ω21 (t) = ⎝ q̇21z 0 −q̇21z 0 q̇21x ⎞ 0 −q̇21x ⎠ 0 (2) (3) The equations expressing the mass center Oc.m.22 of the second link are derived by considering the relationship between the first link’s posture and the angle q22 which rotates around Z21 as follows: r X22 = cos q22 rX21 + sin q22 r Y 21 rY 22 = − sin q22 rX21 + cos q22 rY 21 (4) (5) rZ22 = r Z21 (6) The angular velocity q̇ 22 = (q̇22x , q̇22y , q̇22z )T of the second link, which rotates around Z21 , can be represented by q̇ 22 = q̇22 rZ21 +q22 ṙZ21 . Therefore the mass center Oc.m.22 defined by xm22 = (xm22 , ym22 , zm22 )T can be represented by xm22 = l21 rY 21 + s22 rY 22 . III. DYNAMICS The model of pinching a rigid object with parallel flat surfaces by two robot fingers with 3 DOFs and 3 DOFs is schematically shown in Fig.2. The left finger (finger i = 1) is planar with three actuators rotational around z-axis. The 2500 1 Since each contact point Oi can be expressed by the coordinates ((−1)i li , Yi , Zi ) based on the object frame Oc.m. XY Z, taking an inner product between Equation (11) and r Y gives rise to viscosity direction against spinning motion Z, rZ l1 X r1 O01 rX Y rY Y1 rX Yi = (x0i − x)T rY , i = 1, 2 O c.m. Similarly, it follows that rX Zi = (x0i − x)T rZ , i = 1, 2 Z1 O 2 contact point O 1 contact point Fig. 5. rX , rY , and rZ vectors represent rotational movement of an object. Viscosity works around rX vector at a contact point between a finger tip and an object surface vector q 11 = (q11 , q12 , q13 )T denotes the joint angles of the left hand side finger. In the previous paper [10], it is also assumed that spinning around the opposition axis is possible to arise but viscosity damps rotational motion of the object around x-axis, that is, about ωx , where ω = (ωx , ωy , ωz )T denotes the vector of rigid body rotation in terms of frame coordinates O-xyz (see Figure 2). This viscosity model is effective but rough in a physical sense. Instead of it, we introduce a more faithful viscosity model which is exerted on rotational motion of the object around the rX vector at two contact points between the left or right finger tip and the object surface as shown in Fig.5. At the same time, we introduce the cartesian coordinates Oc.m. -XY Z fixed at the object frame and denote the three orthogonal unit vectors at the object frame in each corresponding direction X, Y , and Z by rX = (rXx , rXy , rXz )T , r Y = (rY x , rY y , rY z )T , and r Z = (rZx , rZy , rZz )T as shown in Fig.2. Next, let us denote the cartesian coordinates of the object mass center Oc.m. by x = (x, y, z)T based on the frame coordinates O-xyz and note that three mutually orthogonal unit vectors fixed at the object frame may rotate dependently on the angular velocity vector ω of body rotation. Then, it is well known that the 3 × 3 rotation matrix R(t) = (r X , rY , rZ ) ∈ SO(3) (7) is subject to the first-order differential equation d R(t) = R(t)Ω(t) dt where ⎛ 0 Ω(t) = ⎝ ωz −ωy −ωz 0 ωx ⎞ ωy −ωx ⎠ 0 (8) (9) Next, denote the position of the center of each hemispherical finger-end by x0i = (x0i , y0i , z0i )T . Then, it is possible to notice that (see Fig.5) xi = x0i −(−1)i (ri −Δxi )r X (12) (10) x = x0i −(−1)i (ri −Δxi + li )r X −Yi rY −Zi rZ (11) (13) A rolling constraint between one finger-end and its contacted object surface can be expressed by the equality of two contact point velocities expressed on either of fingerend spheres and its corresponding tangent plane (that is coincident with one of object flat surfaces) as follows [10]: (r1 − Δx1 ) {ωz − rZz (q̇11 + q̇12 + q̇13 )} = Ẏ1 (14) (r1 − Δx1 ) {−ωy + rY z (q̇11 + q̇12 + q̇13 )} = Ż1 (r2 −Δx2 ) −ωz+rZz q̇21z +rZx q̇21x +rT Z21 r Zq̇22 =Ẏ2 (15) (r2 −Δx2 ) ωy −rY z q̇21z −rY x q̇21x −rT r q̇ Z21 Y 22 =Ż2 The rolling constraint conditions expressed through Equations (14) and (15) are non-holonomic but linear and homogeneous with respect to velocity variables. Hence, Equations (14) and (15) can be treated as Pfaffian constraints [2] that can be expressed with accompaning Lagrange’s multipliers {λY 1 , λZ1 } for Equation (14), and {λY 2 , λZ2 } for Equations (15) in such forms as ⎧ T T ⎪ ẋ+Y Y q +Y ϕ̇+Y ψ̇+Y θ̇ =0 λ ⎪ Y i ϕi ψi θi q i i x i ⎨ T T (16) λZi Z q i q i +Z xi ẋ+Zϕi ϕ̇+Zψi ψ̇+Zθi θ̇ = 0 ⎪ ⎪ ⎩ i = 1, 2 where ⎧ i i ⎪ Y q i = ∂∂Y ⎪ q i − (ri − Δxi ) (−1) rZz eiz + rZx eix ⎪ ⎨ T +rZ21 rZ eiZ21 ∂Y ∂Y ∂Y ⎪ Y xi = ∂ xi , Yϕi = ∂ϕi , Yψi = ∂ψi ⎪ ⎪ ⎩ i i Yθi = ∂Y ∂θ + (−1) (ri − Δxi ), i = 1, 2 and ⎧ i Z q i = ∂∂Z − (ri − Δxi ) (−1)i rY z eiz + rY x eix ⎪ ⎪ q i ⎪ ⎨ T +rZ21 r Y ei2 ∂Zi i Z xi = ∂Z ⎪ ⎪ ∂ x , Zϕi = ∂ϕ , ⎪ ⎩Z = ∂Zi − (−1)i (r − Δx ), Z = ∂Zi , i = 1, 2 ψi i i θi ∂ψ ∂θ and q 1 = (q11 , q12 , q13 )T , q 2 = (q21x , q21z , q22 )T , e1z = (1, 1, 1)T , e2z = (0, 1, 0)T , e1x = 03 , e2x = (1, 0, 0)T , e12 = 03 , and e22 = (0, 0, 1). To simplify notations, we rewrite Equation (16) into λY i Y T i (dX/dt) = 0 , i = 1, 2 (17) T λZi Z i (dX/dt) = 0 T T T where X = (q T 1 , q 2 , x , ϕ, φ, θ) , ⎧ T ⎪ T ⎨ Y1= YT q 1 , 02 , Y x1 , Yϕ1 , Yφ1 , Yθ1 T ⎪ T ⎩ Y 2 = 0, Y T q 2 , Y x2 , Yϕ2 , Yφ2 , Yθ2 2501 (18) and ⎧ T ⎪ T ⎨ Z1 = ZT q 1 , 02 , Z x1 , Zϕ1 , Zφ1 , Zθ1 T ⎪ T ⎩ Z 2 = 0, Z T q 2 , Z x2 , Zϕ2 , Zφ2 , Zθ2 (19) The reproducing force due to finger-tip deformation can be described as (see [13]) fi (Δxi , Δẋi ) = f¯i (Δxi ) + ξi (Δxi )Δẋi (20) where H stands for the constant inertia matrix of the object that must be evaluated on the basis of fixed body coordinates Oc.m. -XY Z, that is, ⎛ ⎞ IXX IXY IXZ H = ⎝ IY X IY Y IY Z ⎠ (28) IZX IZY IZZ Similarly, H2i (i = 1, 2) is given in the following: T (t) H2i = R2i (t)H̄2i R2i where f¯i (Δxi ) = ki Δx2i , i = 1, 2 (21) with stiffness parameter ki > 0[N/m2 ] and ξi (Δxi ) is a positive scalar function of Δxi . The viscosities around rX at two contact points due to spinning motion around the opposing axis is represented by the following Rayleigh’s dissipation functions: ct1 T {ω − (q̇11 + q̇12 + q̇13 )ez } rX 2 (22) Rt1 = 2 ct2 T Rt2 = (ω − q̇21z ez − q̇21x ex − q̇ 22 ) r X 2 (23) 2 Rt = Rt1 + Rt2 (24) where Rt1 expresses the Rayleigh’s dissipation function at the left contact point, Rt2 at the right contact point, both ct1 and ct2 positive constant values, ex = (1, 0, 0)T , and ez = (0, 0, 1)T . The function Rt is derived from taking into considerations that the difference between the rotational velocity of motion of the robot fingers and the rotational velocity of motion of the object relative to the r X vector generates viscosity, and no viscosity arises in the case of equal velocities between the velocity of each robot finger and the velocity of the object relative to the r X vector. The Lagrangian for the overall fingers-object system can be expressed by the scalar quantity L = K − P , where K denotes the total kinetic energy expressed as 1 1 T 1 H1 q̇ 1 + m21 ẋT K = q̇ T m21 ẋm21 + q̇ 21 H̄21 q̇ 21 2 1 2 2 1 + m22 ẋT m22 ẋm22 2 1 T + (q̇ 21 + q̇ 22 ) H̄22 (q̇ 21 + q̇ 22 ) 2 1 1 + M ẋ2 + ẏ 2 + ż 2 + ω T H0 ω (25) 2 2 and P denotes the total potential energy expressed as P = P1 + P2 − M gy + PΔxi (26) where H̄21 similarly stands for the constant inertia matrix of the first link of the robot finger 2 and H̄22 the constant inertia matrix of its second link, that must be expressed on the basis of fixed robot link coordinates Oc.m.2i -X2i Y2i Z2i respectively, that is, ⎞ ⎛ IXX2i IXY 2i IXZ2i H̄2i = ⎝ IY X2i IY Y 2i IY Z2i ⎠ , i = 1, 2 (30) IZX2i IZY 2i IZZ2i where R22 (t) = (rX22 , rY 22 , rZ22 ) ∈ SO(3) H0 = R(t)HRT (t) (27) (31) Thus, owing to the variational principle applied to the form t1 t1 − uT δLdt = i δq i t0 t0 i=1,2 T δX dt − λY i Y T + λ Z Zi i i t1 ∂Rt ∂Δẋi − δX + ξ (Δx )Δ ẋ δX dt i i i T T t0 ∂ Ẋ ∂ Ẋ i=1,2 (32) we obtain a set of Lagrange’s equations of motion of the overall system: 1 ∂Rt T Ḣi + Si q̇ i + Hi q̈ i + − (−1)i fi J0i rX 2 ∂ q̇ i −λY i Y q i − λZi Z q i + g i = ui , i = 1, 2 (33) M ẍ − (f1 − f2 )r X + (λY 1 + λY 2 )r Y ⎛ ⎞ 0 +(λZ1 + λZ2 )r Z − M g ⎝ 1 ⎠ = 0 0 ⎛ ⎞ 0 1 ∂Rt Ḣ0 + S ω+ + f1 ⎝ −Z1 ⎠ H0 ω̇+ 2 ∂ω Y1 ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ 0 Z1 Z2 +f2 ⎝ Z2 ⎠ − λY 1 ⎝ 0 ⎠ − λY 2 ⎝ 0 ⎠ −Y2 l1 −l2 ⎞ ⎞ ⎛ ⎛ −Y1 −Y2 −λZ1 ⎝ −l1 ⎠ − λZ2 ⎝ l2 ⎠ = 0 0 0 i=1,2 where H1 stands for the inertia matrix for finger 1, m21 the mass of the first link of the finger 2, m22 the mass of the second link of it, M the mass of the object, Pi the potential Δx energy of finger i, g the gravity constant, and PΔxi (= 0 i f¯i (ξ)dξ) the potential energy of reproducing force for finger i, and H0 is given in the following: (29) (34) (35) where calculation of partial differentiations of Yi , Zi in ϕ, ψ, θ is presented in Table I. Further, it is possible to see 2502 TABLE I −1 N̂1z = γN 1z PARTIAL DERIVATIVES OF CONSTRAINTS IN (ϕ, ψ, θ). (37) Finally, we interestingly notice six wrench vectors composed of accompaniments to f1 , f2 , λY 1 , λY 2 , λZ1 , and λZ2 in Equations (34) and (35). The six wrench vectors and the external force composed of the last term in Equation (34) work on the 3-dimensional object. IV. C ONTROL SIGNALS A control input realizing stable grasping under the gravity effect without using object kinematics or external sensing, which is called “blind grasping”, is proposed as follows: fd J T (x01 − x02 ) r1 + r2 0i M̂ g ∂y0i −ri N̂iz eiz 2 ∂q i −ri N̂ix eix −ri N̂i2 ei2 , i = 1, 2 M̂ = M̂ (0) + 0 t Differently from the case of rigid finger-ends [11], f0 is not a constant but dependent on the magnitude of Δx1 + Δx2 . Nevertheless, it is possible to find Δxdi (i = 1, 2) for a given fd > 0 so that they satisfy l1 +l2 −Δxd1 −Δxd2 ¯ fd , i = 1,2 (45) fi (Δxdi ) = 1 + r1 + r2 because f¯i (Δx) is of the form of f¯i (Δx) = ki Δx2 (Equation (21)). Substituting this control signals (Equation (39)) into Equations (33), (34), and (35) yields 1 ∂Rt T Ḣi + Si + Ci q̇ i + − (−1)i J0i Δfi r X Hi q̈ i + 2 ∂ q̇ i ΔM g ∂y0i −ΔλY iY q i −ΔλZi Z q i + +ri ΔNizeiz 2 ∂q i +ri ΔNix eix +ri ΔNi2 ei2 +g = 0, i = 1, 2 (46) M ẍ − (Δf1 − Δf2 )r X + (ΔλY 1 + ΔλY 2 )rY +(ΔλZ1 + ΔλZ2 )r Z = 0 (39) T −1 gγM ∂y0i q i dτ 2 i=1,2 ∂q i −1 gγM (y01 (t) + y02 (t) 2 −y01 (0) − y02 (0)) (43) and γM , γN iz (i = 1, 2), γN 2x , and γN 22 are positive constants. The form is nothing but the control signal proposed in the rigid contact case [11] [13]. The third term of the right hand side of Equation (41) is a signal based upon the opposable force between O01 and O02 (not between O1 and O2 , because positions of O1 and O2 can not be measured). The fourth term stands for compensation for the object mass based upon its estimator. The fifth term is introduced for saving excess movements of finger joints from the initial pose. Next define l1 + l2 − Δx1 − Δx2 (44) f0 = fd 1 + r1 + r2 − where (42) 0 From taking inner products between q̇ i and Equation (33), ẋ and Equation (34), and ω and Equation (35), we obtain the relation d q̇ T (K + P ) + 2Rt + ξ(Δxi )Δẋ2i (38) i ui = dt i=1,2 i=1,2 ui = −Ci q̇ i + (−1)i T r1 e1z q̇ 1 dτ −1 = γN 22 r2 (q22 (t) − q22 (0)) from PΔxi (i = 1, 2) and Equations (12) and (13) that ⎧ ∂(PΔx1 +PΔx2 ) = −(−1)i fi JiT rX , i = 1, 2 ⎪ ∂qi ⎪ ⎪ ⎨ ∂(PΔx1 +PΔx2 ) = − (f1 − f2 ) r X ∂x (36) ∂(PΔx1 +PΔx2 ) +PΔx2 ) ⎪ = 0, ∂(PΔx1∂ψ =−f1 Z1 +f2 Z2 ⎪ ⎪ ⎩ ∂(PΔx1∂ϕ +PΔx2 ) = f1 Y1 − f2 Y2 ∂θ Y xi = ∂Yi /∂x = −rY Z xi = ∂Zi /∂x = −rZ 0 t −1 T = rN 1z ri e1z (q 1 (t) − q 1 (0)) t T −1 r2 e2z q̇ 2 dτ N̂2z = γN 2z 0 t −1 N̂2x = γN (ri q̇21x ) dτ 02 0 t −1 N̂22 = γN (r2 q̇22 ) dτ 22 ∂PΔx1 Δx2 = ∂P∂ϕ =0 ∂ϕ ∂Yi T ∂rY = (x − x)T r = Z = (x − x) 0i 0i i Z ∂ϕ ∂ϕ ∂rY ∂Yi T = (x0i − x) ∂ψ = 0 ∂ψ ∂Yi Y = (x0i − x)T ∂r = −(x0i −x)TxX = −(−1)i (ri −Δxi +li ) ∂θ ∂θ ∂rZ ∂Zi T = (x0i − x) ∂ϕ = (x0i − x)T rY = −Yi ∂ϕ ∂Zi Z = (x0i − x)T ∂r = −(x0i −x)TrX = (−1)i(ri −Δxi +li ) ∂ψ ∂ψ ∂Zi Z = (x0i − x)T ∂r =0 ∂θ ∂θ ∂Yi i Yϕi = ∂ϕ = Zi , Zϕi = ∂Z = −Yi ∂ϕ ∂Yi ∂Zi Yψi = ∂ψ = 0, Zψi = ∂ψ − (−1)i (ri − Δxi ) = (−1)i li i Yθi = ∂Y + (−1)i (ri − Δxi ) = −(−1)i li , Zθi = 0 ∂θ = M̂ (0) + (40) (41) 2503 (47) ⎛ ⎞ 0 1 ∂Rt + Δf1 ⎝ −Z1 ⎠ H0 ω̇ + Ḣ0 + S ω + 2 ∂ω Y1 ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ 0 Z1 Z2 +Δf2 ⎝ Z2 ⎠ − ΔλY 1 ⎝ 0 ⎠ − ΔλY 2 ⎝ 0 ⎠ −Y2 l1 −l2 ⎞ ⎞ ⎛ ⎛ ⎛ ⎞ Sx −Y1 −Y2 −ΔλZ1 ⎝ −l1 ⎠ −ΔλZ2 ⎝ l2 ⎠ − ⎝ Sy ⎠ = 0 (48) 0 0 Sz TABLE II where P HYSICAL PARAMETERS OF THE FINGERS AND OBJECT. Mg rXy (49) Δfi = f¯i − f0 − (−1)i 2 fd Mg rY y (50) ΔλY i = λY i + (−1)i (Y1 − Y2 ) − r1 + r2 2 fd Mg rZy (51) (Z1 − Z2 ) − ΔλZi = λZi + (−1)i r1 + r2 2 ΔM = M̂ − M, ΔNiz = N̂iz − Niz , i = 1, 2 ΔN2x = N̂2x − Nx2 , ΔN22 = N̂22 − N22 fd (ri − Δxi ) (Y1 − Y2 )rZz r1 + r2 ri −(Z1 − Z2 )rY z i (ri − Δxi ) M g −(−1) rY y rZz r 2 i −rZy rY z , i = 1, 2 fd (r2 − Δx2 ) N2x = (Y1 − Y2 )rZx r1 + r2 r2 −(Z1 − Z2 )rY x (r2 − Δxi ) M g − rY y rZx r2 2 −rZy rY x fd (r2 − Δx2 ) (Y1 − Y2 )r T N22 = Z21 r Z r1 + r2 r2 −(Z1 − Z2 )rT Z21 r Y (r2 − Δxi ) M g T − r Z21 r Z rY y r2 2 −r T Z21 r Y rZy l11 = l12 = l22 l13 l21 m11 m12 m13 m21 m22 r0 ri (i = 1, 2) L M li (i = 1, 2) h ki (i = 1, 2) cΔi (i = 1, 2) ct1 = ct2 (52) Niz = length length length weight weight weight weight weight link radius radius base length object weight object width object height stiffness viscosity viscosity 0.040 [m] 0.030 [m] 0.060 [m] 0.043 [kg] 0.031 [kg] 0.020 [kg] 0.060 [kg] 0.040 [kg] 0.005 [m] 0.010 [m] 0.063 [m] 0.040 [kg] 0.015 [m] 0.050 [m] 3.000 × 105 [N/m2 ] 1000.0[Ns/m2 ] 5.0 × 10−4 [Nms] TABLE III PARAMETERS OF CONTROL SIGNALS . fd c γM γNiz (i = 1, 2) γN2x γN22 M̂ (0) N̂iz (0)(i = 1, 2) N̂2x (0) N̂22 (0) q21x (0) = q21z (0) (53) internal force damping coefficient regressor gain regressor gain regressor gain regressor gain initial estimate value initial estimate value initial estimate value initial estimate value initial virtual angle 1.000 [N] 0.001 [Nms] 0.050 [m2 /kgs2 ] 5.000 × 10−4 [s2 /kg] 5.000 × 10−4 [s2 /kg] 5.000 × 10−4 [s2 /kg] 0.020 [kg] 0.000 [N] 0.000 [N] 0.000 [N] 0.000[deg] (54) (55) Mg {(Z1 + Z2 )rY y − (Y1 + Y2 )rZy } (56) 2 fd Sy = (r1 − Δx1 + r2 − Δx2 )(Z1 − Z2 ) r1 + r2 Mg {rXy (Z1 + Z2 ) + rZy (l1 − l2 )} − (57) 2 fd Sz = − (r1 − Δx1 + r2 − Δx2 )(Y1 − Y2 ) r1 + r2 Mg {rXy (Y1 + Y2 ) + rY y (l1 − l2 )} + (58) 2 V. N UMERICAL SIMULATION RESULTS AND I NITIAL Sx = and δq21z have a meaning as a virtual displacement but quantity of δq21x and δq21z do not have physical meanings of rotational angels. Hence we set the virtual angles q21x (0) and q21z (0) to zero respectively as shown Table III and the virtual angles do not directly affect numerical simulations at all. The results of numerical simulations, representing key variables of fingers-object system, converge to some constant values as shown in Fig.7. It is confirmed that spinning motion arises but eventually it ceases after 10 seconds, that is, ω → 0 as t → ∞ seen through Figs.6 and 7. On the other hand, if we set the damping parameters ct1 and ct2 to zero respectively, we can see that spinning motion continues eternally. Therefore it is confirmed that motion of the overall fingers-object system is stabilized from the viewpoint of simulations. VALUES We carry out numerical simulations based on the physical parameters of the fingers-object system given in Table II and the parameters of control gains given in Table III in order to confirm the stability of motion of the overall dynamics applied by the proposed control input. It is noted that δq21x 2504 (a) Initial pose Fig. 6. (b) After 10 seconds Motions of pinching a 3-D object under the gravity effect 2 2 2 f1[N] f2[N] λ Y 1[N] 1 1 f1 0 0 5 1 f2 0 10 time[s] 0 5 0 10 time[s] (a) f1 0 (b) f2 λY 2 λZ1 1 0 5 0 10 time[s] 0 5 1 q12[rad/s] 1 0.5 . 0.03 < 5 . q11 The value of zero 10 time[s] 0 5 (g) M̂ 0 1 q21z[rad/s] . . q13 The value of zero 0 5 . . q21x The value of zero -0.5 10 time[s] 0.5 0 0 (j) q̇13 5 0 (k) q̇21x ω y[rad/s] ω x[rad/s] 1 0.5 0 . q22 The value of zero 5 time[s] (m) q̇22 0 ωx T he value of zero -0.5 0 10 10 (l) q̇21z 0.5 0 5 time[s] 1.5 1 1 0.5 0 . q21z The value of zero 10 time[s] 1.5 1.5 -0.5 0 -0.5 5 10 time[s] (n) ωx 0.003 ωy T he value of zero -0.5 0 5 10 time[s] (o) ωy 0.003 1.5 1 ωz The value of zero -0.5 0 5 time[s] (p) ωz Fig. 7. 10 Δ x2[m] 0 0.002 Δ x1[m] ω z[rad/s] 0.002 0.5 0.001 0.001 Δx1 0 0 5 time[s] Δx2 0 10 (q) Δx1 0 5 time[s] R EFERENCES 10 (i) q̇12 0.5 0 5 time[s] 1.5 1 q21x[rad/s] 1 q13[rad/s] -0.5 1.5 0.5 q22[rad/s] 0 (h) q̇11 1.5 VII. ACKNOWLEDGMENTS This work was partially supported by Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research (B) (20360117). 10 time[s] ferently from the previous paper [10], the overall fingersobject dynamics are derived as a full-variables model. It is shown through computer simulations that spinning motion between finger tips and the object arises but eventually stops by virtue of the incorporated viscosity model exerted on rotational motion of the object around rX vector at two contact points between a left or right finger tip and the object surface. Numerical simulation results showed the stability of motion of the overall fingers-object dynamics to which the proposed control input is applied. However, to confirm the effectiveness of our proposed control input in a sound meaning, the analysis of its stability is indispensable and should be carried out from the mathematically reasonable viewpoint. Finally it is shown that the proposed viscosity model plays a crucial role in pinching a 3-D object. . q12 The value of zero 0.5 . 0 -0.5 M 0.02 10 (f) λZ2 1.5 q11[rad/s] M[kg] 0.04 -0.5 5 time[s] (e) λZ1 < . 0 1.5 0.05 . 10 time[s] (d) λY 2 0 λZ2 λ Z2[N] 1 0 10 2 λ Z1[N] 1 5 time[s] (c) λY 1 2 λY 2[N] 2 0 λY 1 10 (r) Δx2 Transient responses of physical variables VI. C ONCLUSION [1] John Napier, Hands, Princeton Univ. Press, Princeton, NJ, USA,1993. [2] R. M. Murray, Z. Li, and S. S. Sastry, A Mathematical Introduction to Robotic Manipulation, CRC Press, Boca Raton,FL, USA and Tokyo, Japan, 1994. [3] M. R.Cutkosky, Robotic Grasping and Fine Manipulation, Kluwer Academic, Dordrecht, Netherlands, 1985. [4] A. Bicchi, “Hands for dexterous manipulation and robust grasping: A difficult road toward simplicity,” IEEE Trans. on Robotics and Automation, Vol.16, No. 6, pp.652–662, 2000. [5] D.J. Montana, “The kinematics of contact and grasp”, Int. J.of Robotics Research, Vol. 7, No. 3, pp.17-32, 1988. [6] D.J. Montana, “Contact stability for two-fingered grasps”, IEEE Trans. on Robotics and Automation, vol.8, no.4, pp.421-430,1992. [7] A.A. Shabana, Computational Dynamics, Second Edition, WileyInterscience, New York, USA, 2001. [8] S. Arimoto, P.T.A. Nguyen, H.-Y. Han, and Z. Doulgeri, “Dynamics and control of a set of dual fingers with soft tips”, Robotica, vol.18, no.1, 2000, pp.71-80. [9] S.Arimoto, K.Tahara, J.-H.Bae, M.Yoshida, “A stability theory of a manifold: concurrent realization of grasp and orientation control of an object by a pair of robot fingers”, Robotica, Vol.21, No.2, pp.163-178, 2003. [10] S.Arimoto, M.Yoshida, J.-H.Bae, “Modeling of 3-D object manipulation by multi-joint robot fingers under non-holonomic constraints and stable blind grasping”, JSME Journal of System Design and Dynamics, Vol.1, No.3, pp.434-446, 2007. [11] S. Arimoto and M. Yoshida, “Modeling and Control of ThreeDimensional Grasping by a Pair of Robot Fingers”, SICE J. of Control, Measurement, and System Integration, Vol.1, No.1, pp.2-11, 2008. [12] M. Yoshida, S. Arimoto, and Z. W. Luo, “Three-Dimensional Object Manipulation by Two Robot Fingers with Soft Tips and Minimum D.O.F”, Proc. of the 2008 IEEE Robotics and Automation, Pasadena, CA, May 19-23,pp.4707-4714, 2008. [13] S. Arimoto Control Theory of Multi-fingered Hands, Springer-Verlag, London, 2008. [14] Gerard J. Tortora and Sandra R. Grabowski Introduction to the human body:The essentials of anatomy & physiology, Wiley, NJ, USA, 2004. A saddle joint model with orderless actuations and rolling constraints have been treated in a faithful manner and incorporated into the overall fingers-object system. It is shown that 3-D pinching by two robot fingers, one is a 3-DOFs planar finger (resembles the index finger) and the other is a 3-DOFs finger with a saddle joint (the thumb), is performed numerically by using the derived computational model. Dif- 2505