Morphological optimization of prosthesis finger for precision - - PowerPoint PPT Presentation

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Morphological optimization of prosthesis’ finger for precision grasping of little objects

• J. L. Ramírez1, A. Rubiano1, N. Jouandeau2
• L. Gallimard1, O. Polit1

1LEME Université Paris Ouest Nanterre La Défense, France

{ jl.ramirez_arias, astrid.rubiano, laurent.gallimard, olivier.polit } @u-paris10.fr

2LIASD, Université Paris 8, France

n@ai.univ-paris8.fr

July 2015

1/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Plan

1

Introduction

2

Modeling of the robotic hand prosthesis’ finger Description of the robotic hand prosthesis’ finger Kinematic model Dynamic model

3

Finger prototype test platform set-up Materials and methods Kinematic tracking and force measure

4

Morphology optimization Evolution process Evaluation process Experiment

5

Results

6

Conclusions and Perspectives

2/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Soft Robotics

Classical Robots Rigid structures Soft Robots [Nurzaman et al., 2013] Elastic and deformable bodies Unconventional materials [Andrianesis and Tzes, 2013] Improve interactions with the environment UB-HAND IV [Palli et al., 2012; Ficuciello et al., 2014] Pisa-IIT Soft Hand [Ajoudani et al., 2013]

3/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Robot Features Tendon driven mechanisms Flexible links Smooth joints Morphological analysis [Jouandeau and Hugel 2013-2014] To reach better synergies between movement primitives and limbs lengths Applied to NAO humanoids

To validate parts dimension on real To design primitives in simulation

4/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Description of the robotic hand prosthesis’ finger Kinematic model Dynamic model

Tendon-driven finger composed of three joints: Metacarpophalangeal (MP or MCP) - θ33 Proximal interphalangeal (PIP) - θ35 Distal interphalangeal (DIP) - θ36 Under-actuated ⇒ one servo motor ⇒ angle joints relations: θ35 = 0.23θ33 θ36 = 0.72θ33

Fastening point Fastening point Flexion tendon Extension tendon DIP PIP MP Flexion - Extension Pulley Servo Motor Up - Down 5/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Description of the robotic hand prosthesis’ finger Kinematic model Dynamic model

Denhavit-Hartenberg - Khalil and Kleinfinger (DHKK)

Link αi ai di θi 33 −π/2 θ33 34

π/2

θ34 35 −π/2 l32 θ35 36 l33 θ36 f l34

0Tn = n

∏

i=1 i−1Ti =

• 0Rn

0Pn

1

• 𝜾𝟒𝟒

𝜾𝟒𝟓 𝜾𝟒𝟔

𝒚𝒈 𝒛𝒈 𝒜𝒈

𝜾𝟒𝟕

𝒚𝟒𝟕 𝒛𝟒𝟕 𝒜𝟒𝟕 𝒚𝟒𝟔 𝒛𝟒𝟔 𝒜𝟒𝟔 𝒚𝟒𝟓 𝒛𝟒𝟓 𝒜𝟒𝟓 𝒚𝟒𝟒 𝒛𝟒𝟒 𝒜𝟒𝟒

𝒎𝟒𝟓 𝒎𝟒𝟒 𝒎𝟒𝟑

6/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Description of the robotic hand prosthesis’ finger Kinematic model Dynamic model

Virtual displacements and virtual works

δWe δWi

• Virt. Works

= = QT

e

M¨ qT Forces δre δri

• Virt. Disp. of q

⇓

Dynamic equilibrium δqT[M¨ q −Qe] = 0

⇓

Input torque τ33(fR,q, ˙ q, ¨ q)

𝒛𝟒𝟒 𝒚𝟒𝟒

𝜾𝟒𝟒 𝜾𝟒𝟔 𝜾𝟒𝟕

𝒛𝟒𝟔 𝒚𝟒𝟔 𝒛𝟒𝟕 𝒚𝟒𝟕 𝒈𝑺 𝒙𝟒𝟑 𝒙𝟒𝟒 𝒙𝟒𝟓

7/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Materials and methods Kinematic tracking and force measure

The experiments seek to:

1

Track the kinematics = ⇒ CCD camera Prosilica GE-2040

2

Measure fingertip force = ⇒ Flexiforce Sensor

3

Evaluate tendon driven dynamic = ⇒ Using different motors (classical and serial actuactors, from 2.3Kg-cm to 101Kg-cm, from Traxxas to Dynamixel)

Interchangeable Actuator Adjustable finger position

8/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Materials and methods Kinematic tracking and force measure

Finger position overshoots

The 0Px

f vector shows perturbations after contact

Sample experiment with Traxxas actuator (2.3Kg-cm): The lengths of the finger could:

Increase the amount of torque needed Impact the precision of the grasping

9/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Evolution process Evaluation process Experiment

Find Optimal finger’s phalanges lengths ⇐ ⇒ Reach a constant fR of 5N Min position error Min input torque τ33 Morphological Optimization Evolution process based on an heuristic evaluation Simulation of Kinematic of our finger Simulation of Dynamics of our finger

10/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Evolution process Evaluation process Experiment

Motors, Torques < M,T > and lengthsnew as parameter values Algorithm 1 evolution < M,T >(n, H , eval)

1: (H , L ) ← (/ 0, / 0); 2: for i = 0 to n do 3: lengthsnew ← newParam < M,T >(H ); 4: (d, m) ← move (lengthsnew, qinitial, qobj, U, dt); 5: score ← eval (d, m); 6: if score == ACCEPT then 7: insert ((lengthsnew , score), L ); 8: end if 9: insert ((lengthsnew , score), H ); 10: end for 11: return best (L );

11/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Evolution process Evaluation process Experiment

Evaluation of positioning error d and input torque m (i.e. τ33) Algorithm 2 eval (d, m)

1: if d < dbest then 2: (dbest, mbest) ← (d, m); 3: return ACCEPT; 4: else if m ≥ 0 then 5: if m < mbest then 6: (dbest, mbest) ← (d, m); 7: return ACCEPT; 8: end if 9: end if 10: return REJECT;

12/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Evolution process Evaluation process Experiment

Algorithm 3 kinematicMove (lengthsnew, qinitial, qobj, U, dt)

1: q ← qinitial; 2: t ← 0; 3: while contact (q) == false do 4:

(u, t) ← next (U, t, dt);

5:

q ← f (lengthsnew, q, u, dt);

6: end while 7: return (dist (q, qobj), −1);

13/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Evolution process Evaluation process Experiment

Algorithm 4 DynamicMove (lengthsnew, xinitial, qobj, fR, U, dt)

1: q ← position (xinitial); 2: x ← xinitial; 3: t ← 0; 4: while contact (q) == false do 5: (u, t) ← next (U, t, dt); 6: x ← g (lengthsnew, x, u, dt); 7: q ← position (x); 8: end while 9: while torque (x) < fR do 10: (u, t) ← next (U, t, dt); 11: x ← g (lengthsnew, x, u, dt); 12: end while 13: return (dist (q, qobj), u);

14/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Starting from (36.58, 24.20, 25)[mm] and 150[Nmm] After 150 tests

𝑁

𝑔

𝑁36 𝑁35 𝑁33

l32[mm] l33[mm] l34[mm] τ33[Nmm] 22.1 19.6 16 46 26.5 15.3 13.3 58.6 26.2 10 18.9 55.1 23.1 12.9 10.6 52.3 22.9 12.8 10.3 51.8 18.9 9.9 13.1 40.3 22.2 9.2 10 50.7 15/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Conclusions Improvements (of size, torque and energy consumption) Dynamic modeling and optimization Adaptive force grasping optimization Generation of smooth trajectories Perspectives Torque control based on the performed optimal analysis of the morphological parameters New finger with soft and flexible parts Grasping mechanism optimization according to usage

16/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives

Morphological optimization of prosthesis’ finger for precision grasping of little objects

• J. L. Ramírez1, A. Rubiano1, N. Jouandeau2
• L. Gallimard1, O. Polit1

1LEME Université Paris Ouest Nanterre La Défense, France

{ jl.ramirez_arias, astrid.rubiano, laurent.gallimard, olivier.polit } @u-paris10.fr

2LIASD, Université Paris 8, France

n@ai.univ-paris8.fr

July 2015

17/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger

Introduction Modeling of the robotic hand prosthesis’ finger Finger prototype test platform set-up Morphology optimization Results Conclusions and Perspectives Ajoudani, A., Godfrey, S., Catalano, M., Grioli, G., Tsagarakis, N., and Bicchi, A. (2013). Teleimpedance control of a synergy-driven anthropomorphic hand. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1985–1991. Andrianesis, K. and Tzes, A. (2013). Design of an innovative prosthetic hand with compact shape memory alloy

• actuators. In 21st Mediterranean Conference on Control Automation (MED), pages 697–702.

Ficuciello, F., Palli, G., Melchiorri, C., and Siciliano, B. (2014). Postural synergies of the {UB} hand {IV} for human-like grasping. Robotics and Autonomous Systems, 62(4):515 – 527. Nurzaman, S., Iida, F., Laschi, C., Ishiguro, A., and Wood, R. (2013). Soft robotics [tc spotlight]. Robotics Automation Magazine, IEEE, 20(3):24–95. Palli, G., Scarcia, U., Melchiorri, C., and Vassura, G. (2012). Development of robotic hands: The ub hand evolution. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5456–5457. 18/18 Nicolas Jouandeau Morphological optimization of prosthesis’ finger