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공학석사 학위논문

Modeling of Tendon Driven Soft

Wearable Robot for the Finger

텐던 드리븐 메커니즘을 이용한 유연한 입는형

손가락 로봇의 모델링

2013년 2월

서울대학교 대학원

기계항공공학부

강 병 현

i

Abstract

Modeling of Tendon Driven Soft Wearable Robot for the Finger

Brian Byunghyun Kang

School of Mechanical and Aerospace Engineering

The Graduate School

Seoul National University

This paper presents two ways to increase controllability of tendon driven

soft wearable robot for the finger. Tendon Anchoring Support (TA Support)

was developed to be fixed to the hand to transmit force from motor to the

target actuation point of the robot. TA Support was developed with several

design considerations, especially customization to maximize fixation to

individual patient’s hand. For that, fabrication process for customization to

patient’s hand has been established and introduced in this paper.

This paper introduces deformation model for posture estimation and

force estimation model. After development of TA Support, to increase the

controllability of the robot, deformation model for the MCP joint flexion has

been built to consider deformation of glove and wire elongation. Experiments

have been conducted to complete deformation model. Based on MCP joint

flexion deformation model, force estimation for MCP joint flexion has been

built. To verify these two models, MCP joint posture estimation experiment

ii

and force estimation experiment have been conducted.

Engineers developing the soft wearable robot with tendon driven

mechanism will always encounter problems to control the robot, and as stated

in this paper, this paper will show prospective view to model and control soft

exoskeleton

Keywords: Soft exoskeleton model, SNU Exo-Glove, Tendon Anchoring

Support, MCP joint flexion model, MCP joint posture estimation, MCP

joint force estimation

Student Number: 2011-20680

iii

Contents

Abstract .................................................................................... i

Chapter 1 Introduction .......................................................... 1

Chapter 2 Force Transmission Analysis ............................... 4

2.1 Comparison of Conventional Mechanisms ............................. 4

2.2 Development of Tendon Anchoring Support .......................... 7

Chapter 3 Tendon Anchoring Support ................................ 13

3.1 Design Considerations .......................................................... 13

3.1.1 Small and Compact ............................................................. 13

3.1.2 Position of TA Support ........................................................ 13

3.1.3 Fixation ............................................................................... 14

3.1.4 Customization ..................................................................... 14

3.2 Manufacturing Process .......................................................... 15

Chapter 4 Deformation of the Glove .................................. 20

4.1 Direct Attachment to Link Case ............................................ 20

4.1.1 TA Support Movement ........................................................ 20

4.1.2 Palm Velcro Strap Movement ............................................. 21

4.1.3 Finger Attachment Point Movement ................................... 21

4.1.4 Wire Elongation .................................................................. 22

4.2 Wire Passing Velcro Strap Case ............................................ 22

iv

Chapter 5 Modeling ............................................................ 29

5.1 Model for Wire Attachment at MCP Joint ............................ 29

5.2 Model for Force Estimation of MCP Joint ............................ 31

Chapter 6 Experiment ......................................................... 35

6.1 Experimental Setup ............................................................... 35

6.2 Spring Constant Estimation .................................................. 35

Chapter 7 Posture and Force Estimation ............................ 47

7.1 Posture Estimation ................................................................ 47

7.1.1 Constant Force Applied ....................................................... 47

7.1.2 Random Force Applied ....................................................... 48

7.2 Force Estimation ................................................................... 49

Chapter 8 Conclusion ......................................................... 54

Bibliography .......................................................................... 56

국문초록 ............................................................................... 60

v

List of Tables

Table 6.1 Spring constant estimation result ................................................ 41

vi

List of Figures

Figure 2.1 Conventional hand exoskeleton mechanism: (a)

musculoskeletal structure of human finger, (b) joint and link

mechanism, (c) pneumatically actuating mechanism, (d) joint-

less tendon driven mechanism ..................................................... 11

Figure 2.2 Tendon Anchoring Support force transmission analysis ............. 12

Figure 3.1 Part of the hand where TA Support should be placed .................. 17

Figure 3.2 Concept of keeping distance between the fingertip and TA

Support ........................................................................................ 18

Figure 3.3 Tendon Anchoring Support manufacturing process: (a) Casted

hand, (b) 3D Scanned hand file, (c) TA Support design in

CAD file, (d) Final product made by 3D Printer ......................... 19

Figure 4.1 Two cases of deformation of the glove: (Solid Circle) Direct

attachment to link case, (dotted Circle) Wire passing Velcro

strap case ..................................................................................... 24

Figure 4.2 TA Support movement modeling ................................................ 25

Figure 4.3 Palm Velcro strap movement ....................................................... 26

Figure 4.4 Finger attachment point movement ............................................. 27

Figure 4.5 Wire elongation ........................................................................... 28

Figure 5.1 MCP joint wire attachment model for flexion ............................. 33

Figure 5.2 Model for force estimation of MCP joint .................................... 34

Figure 6.1 Schematic of experimental setup ................................................. 42

Figure 6.2 Wire tension vs. Actuated wire length for different angles ......... 42

Figure 6.3 Actuated wire length vs. wire tension for four factors of

deformation for MCP joint angle 17˚ ....................................... 43

Figure 6.4 Actuated wire length vs. wire tension: Comparison between

experimental result(blue dots) and modeling estimation(red

vii

dots) ............................................................................................. 44

Figure 6.5 Initial actuation position estimation using Least Square

Method ................................................................................ 45

Figure 6.6 Wire tension vs. actuated wire length: Comparison among

deformation model(blue solid line), rigid model(colored

dotted line) and experimental result(colored solid line) .............. 46

Figure 7.1 MCP joint angle comparison between experimental result and

posture estimation by deformation model: Constant force

applied ......................................................................................... 51

Figure 7.2 MCP joint angle comparison between experimental result and

posture estimation by deformation model: Random force

applied ......................................................................................... 52

Figure 7.3 Comparison between experimental result and MCP force

estimation at MCP joint angle 25˚ ............................................ 53

1

Chapter 1. Introduction

The main reasons of physical disabilities in hands are C5 and C6 spinal

cord injuries (SCIs) and stroke. These patients have good movement from

shoulder to wrist, but no hand movement at all. Many researches have

attempted to build wearable robotic hands for assistance in daily life motions

and rehabilitation for these patients.

Many wearable robotic hands attempted to support the hand of the patients

and to transmit actuation forces by conventional pin joints and rigid frames.

In order to transmit the force from the robot to patient’s finger, it is

important for robot joints and finger joints to have coaxial joint. However,

due to scarce gap between the fingers, having robot joints on the side of the

fingers are not possible. To resolve this problem, many robots decided to put

joints and link frames on the backside of the hand [1, 2]. Due to these

transmission links at the back of the hand, robots get bulky and hard to wear.

To overcome issues of joint and link mechanism, several joint-less

wearable robotic hands have been developed with pneumatic actuation

mechanism [3, 4] and tendon driven mechanism [5, 6] instead of

conventional joint and link actuation mechanism. Pneumatically controlled

robotic hands have settled the problems of complexity of the robot, but

2

necessity of large pump to actuate the pneumatic system is limitation to

decrease the size of the robot.

Joint-less robotic hand with tendon driven mechanism is one solution to

develop a wearable robot with compact and simple structure, because wire is

small and flexible structure that can transfer force from motor to target. To

have actuation in this mechanism, wire has to be fastened in both distal and

proximal part of the joint so that joint actuation can be done by controlling

the wire length, as if muscle in human musculoskeletal structure. This

mechanism can be used to develop a wearable robot for any part of the

human body. To fulfill the compactness criteria of the wearable robotic hand,

SNU Exo-Glove with glove and joint-less tendon driven mechanism has

been developed [6, 7]. However, unlike human, only one wire is used in

SNU Exo-Glove flexion movement and this is the limitation to control

fingertip force precisely. Controlling the fingertip force and direction can

facilitate more variety grasping objects and finger actions.

Beyond to this, overall soft exoskeletons have serious problems in control,

including SNU Exo-Glove. Due to flexibility of glove, actuating wire causes

deformation of glove and rigid models become impracticable in soft

exoskeletons.

Even though it is impossible to consider all the deformation factors of

3

SNU Exo-Glove, attempt has been made to build simple model to overcome

major factors of deformations in SNU Exo-Glove, glove and wire

deformations. In order to analyze the deformations in the SNU Exo-Glove in

detail, new robot with one flexion wire in MCP joint has been made and

used in experiments for this paper. To build the model to control the index

fingertip force and force direction with flexion and extension wire in each

joint, this paper introduces the first step of deformation model. The model

has been built to estimate the actuated wire length with wire tension for

certain metacarpophalangeal (MCP) joint angle in flexion. Based on this

model, the force and force direction of MCP joint can be predicted with wire

actuation length and wire tension. This paper also introduces Tendon

Anchoring Support (TA Support) [8], which was necessarily developed to

transmit the force from motor to the fingertip.

4

Chapter 2. Force Transmission Analysis

2.1 Comparison of Conventional Mechanisms

As mentioned in the introduction, there are several different mechanisms

to actuate wearable robotic hand. Figure 2.1 shows the musculoskeletal

structure of human finger and three different types of actuation mechanism

of wearable robotic hand.

Figure 2.1(a) is musculoskeletal structure of human finger. One end of the

tendon is attached to the surface of the bone and the other end of the tendon

is attached to the muscle. While one end of the muscle is attached to the

tendon, the other end of the muscle is attached to the palmar bone of the

hand or the lower arm bone. Contracting the muscle will apply force F to the

tendon in proximal direction. This force is transmitted to the point where the

tendon is attached to the finger bone and the finger is actuated either flexion

or extension. There exists several different tendons in a finger and each

tendon path is determined by few pulleys as shown in the figure. Pulleys are

the annular ligaments of the fingers that are attached to the bone to set path

for the tendons.

Figure 2.1(b) is one of the conventional joint and link mechanism. To

5

actuate finger, it is important for robot and hand to have coaxial joint. This

implies that conventional joints have to be built on side of the finger.

However, joints on the side of the finger will interfere with nearby fingers.

Due to this reason, mostly, wearable robotic hands with conventional joint

and link mechanism have built on backside of the fingers. Conventional joint

and link mechanism robots are developed either to have robot and finger

joints to be coaxial or to have four bar linkage structure instead of coaxial

robot joints [9-13]. Figure 2.1(b) shows the latter case. Actuating each

linkage applies forces in normal direction to the linkages. Due to the

direction of the force acting on the finger, structures that hold links to the

finger do not have to be seriously tightened. If the robot is applying shear

direction force on the finger, slippage will occur while actuating unless

finger is seriously tightened to the finger. When designing this mechanism,

change of axis of linkage joint makes hard to align with axis of actual finger

joint. Also, due to structures on backside of the hand, wearable robotic hand

cannot be compact.

Figure 2.1(c) is pneumatically actuating mechanism [14-16]. As

mentioned in previous paragraph, structures cannot be implemented on the

sides of the finger. Therefore, air tubes are also mounted on backside of the

finger. Air tubes that are used in these robots are bent in one direction when

6

air pressure in the tube is increased. Using this characteristics, robots can

actuate fingers to grasp objects. However, it is not easy to control fingers and

finger joints individually, because additional air pumps or valves with

motors are needed to control individually. The robots with this mechanism

are smaller than conventional joint and link mechanism, but still have

limitation to decrease the size of the robot.

Figure 2.1(d) is joint-less tendon driven mechanism [6-7, 17]. Developed

SNU Exo-Glove, composed of only glove and wire, uses this mechanism.

This mechanism is inspired by musculoskeletal structure of human finger.

As shown in the figure 2.1(d), wire works as tendon and paralyzed hand

works as finger bone. Teflon tubes have been used to take role of finger

pulleys and one end of wire is fixed at the end of the glove to work as tendon

attached to the finger bone. As shown in the figure 2.1(d), in order to

transmit the force to the fingertip, the other end of the wire has to be fixed on

hand as if muscle is attached to the palmar bone of the hand. To fulfill this

function, a structure, Tendon Anchoring Support (TA Support) has been

developed. Since the wire is directly linked to the motor, TA Support should

fix motor on the hand. However, instead of fixing motor onto the hand, one

end of the sheath is fixed onto the hand, while the other end of the sheath is

fixed to the motor system. Not deformable in longitudinal direction

7

characteristic of sheath makes motor, sheath and TA Support as one body

and works as if one end of the wire is fixed to the palmar part of the hand.

By fixing TA Support to the hand, actuating motor will work as muscle

contraction and transmit the wire tension to the fingertip. Using joint-less

tendon driven mechanism, glove and tendons are the only components that

are mounted on fingers, which it makes the robot compact.

However, there are several issues that have to be solved such as wire path

routing, force transmission, deformation of hand and glove, fabrication.

Main function of TA Support is to fix one end of the sheath to the palm and

to transmit the actuation force to the fingertip. When developing wearable

robot for any parts of the human body, it is unavoidable to meet force

transmission problem. To solve this problem, it is necessary to develop a

structure like TA Support to fix actuation system on some part of the body.

Such structure as TA Support should be designed to be small and compact

and to be fixed well on some part of the body without applying high pressure.

Further explanations on force transmission by TA Support will be explained

in following section and design considerations and fabrication process for

TA Support have been stated in following chapter.

2.2 Development of Tendon Anchoring Support

8

To grasp an object by actuating fingers, fixing TA Support to the hand is

very important to transfer the wire tension force to the fingertip. Figure 2.2

shows the schematic of the force transfer from the motor to fingertip. One

end of the wire is attached to the index fingertip and Fgm is the wire tension

acting on the fingertip. Fm is the force of the motor that pulls the wire. Ffriction

is the friction force acting between the sheath and the wire. Fms is the force

acting on TA Support.

Motors are implemented in the motor system frame and this motor system

frame is connected to TA Support by sheath in between. Therefore, TA

Support and the sheath and the motor system can be treated as one body. In

order not to lose actuation displacement, sheath should not be deformable in

longitudinal direction, in direction of Ffriction.

For further understanding of TA Support and other components, force

relation is important. Due to Ffriction between the wire and the sheath,

equation becomes

frictiongmm FFF . (2.2.1)

Since TA Support and the motor system is one body, actuating the motor

will pull the motor system frame and TA Support toward the fingertip. Since

SNU Exo-Glove uses Teflon tube and titanium wire to minimize the friction

9

force between the sheath and the wire, assumption has been made to neglect

friction. Based on this assumption, the force acting on TA Support is same as

the wire tension acting on the fingertip,

mms FF . (2.2.2)

Same force transfer mechanism occurs for both finger flexion and

extension.

In figure 2.2, if there is no TA Support, actuating the motor will pull up

the sheath all the way up to the fingertip instead of actuating finger. For that,

TA Support fixation to the hand is essential for force transfer.

If TA Support is not well fixed to the hand, actuation displacement loss

will occur and be problem in controlling the fingers. The more actuation

displacement loss occurs, the system gets more nonlinear. It is impossible to

eliminate actuation displacement loss, but minimizing it to reduce

nonlinearity through fabrication process is very important. Another problem

caused by not well fixed TA Support is decrease in range of motion of the

fingers. As TA Support moves closer to the fingers, it will be much harder to

grasp or pinch object due to the limit range of finger motion. As soon as TA

Support is fixed, the wire tension will be directly delivered to the fingertip

and actuate finger.

10

Assuming that the TA Support is fixed, there are several other points in the

glove that causes deformation. For instance, Teflon tubes are embedded with

Velcro straps on palmar part and finger part of the glove as to set path with

small friction. When tension is applied to the wire, wire tends to straighten

between the fingertip and the TA Support. Due to this phenomenon, Velcro

straps are drawn away from the finger and palm due to the deformation of the

glove. Also, the point where the wire is attached at the finger moves as tension

of wire increases.

11

Figure 2.1 Conventional hand exoskeleton mechanism: (a)

musculoskeletal structure of human finger, (b) joint and link mechanism,

(c) pneumatically actuating mechanism, (d) joint-less tendon driven

mechanism

12

Figure 2.2 Tendon Anchoring Support force transmission analysis

13

Chapter 3. Tendon Anchoring Support

Based on the force transmission analysis, development of TA Support was

unavoidable. After several designs try outs, four important design

considerations have been established, which are small and compact, position

of TA Support, fixation and customization. For need of customizing TA

Support for individual patients, following manufacturing process has been

developed. Prototype of TA Support has been made for developer’s hand.

3.1 Design Considerations

3.1.1 Small and Compact

This design consideration has been arisen from beginning of SNU Exo-

Glove development, which was designed to be compact and easy to wear and

to take off. Having a small and compact size of TA Support is necessary not

to disturb from grasping or pinching.

3.1.2 Position of TA Support

Position of TA Support is very critical to the design of TA Support. Since

TA Support should not be interrupting grasping or pinching motions, TA

Support should be below the metacarpophalangeal joint of the thumb (dotted

14

line in figure 3.1). TA Support also should not interfere with wrist

movement, which interprets that TA Support should be above the wrist joint

(solid line in figure 3.1). If TA Support is placed below the solid line, the

distance between the fingertip and TA Support will change according to the

wrist movement and will be unable to control.

3.1.3 Fixation

As mentioned in previous section, fixing TA Support is necessary to

transfer the wire tension to the fingertip. While actuating SNU Exo-Glove

index finger, previous TA Support had fixation problem and was not able to

actuate finger well.

The most important function of TA Support is keeping the same distance

between the fingertip and the end of the sheath. TA Support is designed to

fix one end of the sheath to the hand. Finger will not be actuated unless the

distance between fingertip and TA Support is maintained. As long as one

end of the sheath is fixed to TA Support, sheath and motor system does not

have to be fixed to anything. Figure 3.2 shows the concept.

3.1.4 Customization

This design consideration has been arisen to prevent decubitus ulcer and

15

better fixation. By definition of pressure, having a larger area of contact area

for same amount of acting force will have less pressure acting on the hand. In

other words, by customizing TA Support, contact area of TA Support can be

increased and this can reduce the pressure acting on the hand for the same

actuation force. Less pressure acting on the hand means better chance to

prevent the injuries. Also, customized TA Support can hold up more forces

than non-customized design. This implies range of motor actuation force,

range of grasping force, can be increased by increasing the contact area

between the hand and TA Support.

3.2 Manufacturing Process

For need of customizing TA Support for individual patients, following

manufacturing process has been developed. Prototype of TA Support has

been made based on developer’s hand.

The first procedure of manufacturing TA Support is to cast a hand of a

patient. Due to the limit of accessibility to patients while designing TA

Support, casting a patient’s hand is good way to start. Alginate has been used

as a hand mold and urethane has been poured into this alginate mold to cast

patient’s hand. The benefit of this procedure is that it takes only five minutes

16

to make patient’s hand mold with alginate. Figure 3.3(a) shows the actual

casted hand.

The next step is to scan the casted hand in 3D. Scanned file will be used in

CAD program in two ways. First, base parameters for TA Support will be

drawn from this scanned file. Second, after TA Support CAD file is designed,

to check how well TA Support fits to patient’s hand, interference check

between the 3D scanned file and TA Support CAD file will be performed.

Figure 3.3(b) shows 3D scanned file of casted hand in figure 3.3(a).

Based on the 3D scanned file of the hand, TA Support is designed in CAD

program. The cross section of the hand for every 5mm has been taken from

CAD program. For each cross section, an ellipse that best fits this cross

section has been drawn. Based on these ellipses, TA Support is created into

CAD model. This CAD model is, then, compared to the 3D scanned hand

file to see how well it fits to patient’s hand. Figure 3.3(c) shows TA Support

CAD file with the 3D scanned file.

CAD model of TA Support is printed in 3D through rapid prototyping

machine (3D printer). Material of the product is acrylic plastic and strong

enough to use as a part of SNU Exo-Glove. Figure 3.3(d) shows the final

product of TA Support attached to the glove.

17

Figure 3.1 Part of the hand where TA Support should be placed

18

Figure 3.2 Concept of keeping distance between the fingertip and TA

Support

19

Figure 3.3 Tendon Anchoring Support manufacturing process: (a)

Casted hand, (b) 3D Scanned hand file, (c) TA Support design in CAD

file, (d) Final product made by 3D Printer

20

Chapter 4. Deformation of the Glove

To control the fingertip force and force direction, four wires have to be

attached to each phalange of finger to actuate three joints,

metacarpophalangeal (MCP) joint, proximal interphalangeal (PIP) joint and

distal interphalangeal (DIP) joint [18]. Even though wire path for each joints

are different, causes of nonlinearity including deformation of glove and TA

Support and other factors can be divided into two cases. One is when the

wire is attached to the link and the other is when the wire is passing through

the pulley of the link. Figure 4.1 shows direct attachment to link points (solid

circles) and wire passing Velcro strap points (dotted circles).

4.1 Direct Attachment to Link Case

4.1.1 TA Support Movement

Even though TA Support has been developed to be well fixed to the hand,

it is impossible to fix perfectly. As explained in force transmission analysis,

force acting on TA Support pushes it toward fingertip and still moves due to

the compliance of palm skin. Figure 4.2 shows TA Support movement and

which part of the deformation model is. TA Support is assumed to be

21

connected to imaginary frame that is fixed to hand with linear spring.

4.1.2 Palm Velcro Strap Movement

As mentioned in chapter 2. Force transmission analysis, tension in wire

straightens the wire between the wire attachment point and TA Support. This

phenomenon pulls the palm pulley away from the palm. Movement of palm

pulley changes the wire path from TA Support to wire attachment point.

Figure 4.3 shows how palm Velcro strap movement occurs. Similar to TA

Support movement, palm Velcro strap is assumed to be fixed to imaginary

frame that is fixed to hand and connected with linear spring. Palm Velcro

strap is assumed to be point in deformation model.

4.1.3 Finger Attachment Point Movement

The point where the wire is attached to the link moves when the wire is

actuated. Current SNU Exo-Glove winded the wire around the finger instead

of directly attaching the wire to the glove. By winding the wire around the

finger, deformation of the glove has been drastically reduced. However, still

due to the compliance of the skin, wire attachment point tends to move

toward palm Velcro strap. Figure 4.4 shows finger attachment point

movement and how they deform. Due to the compliance of hand and glove,

22

shape of wire winding finger change and attachment point move toward

palm Velcro strap. This phenomenon is also assumed to be linear spring

motion.

4.1.4 Wire Elongation

Robot in this paper used 0.5 mm diameter titanium wire with nylon

coating. The wire has been chosen to reduce friction and to be kink-free. The

wire chosen to satisfy these criteria has one big weakness, which tends to

elongate as force is applied to wire.

Figure 4.5 shows which part of deformation model is wire elongation and

result of tensile stress experiment. Wire elongation was tested by tensile

strength experiment with three different length specimens. Result came out

to be very close to linear motion under 40N as wire length increase. Based

on tensile strength result, linear spring constant was estimated and was

implemented on deformation model.

4.2 Wire Passing Velcro Strap Case

Similar to the palm Velcro strap movement, Velcro strap attached to the

link is pulled away from the link as tension is applied to the wire. This effect

23

will change the wire attachment point and change the geometry of the wire

path. However, this effect is expected to be minor to the previous case, since

this only changes the wire attachment point. Deformation model in this

paper does not consider this case. Model considering this case will be future

work.

24

Figure 4.1 Two cases of deformation of the glove: (Solid Circle) Direct

attachment to link case, (dotted Circle) Wire passing Velcro strap case

25

Figure 4.2 TA Support movement modeling

26

Figure 4.3 Palm Velcro strap movement

27

Figure 4.4 Finger attachment point movement

28

Figure 4.5 Wire elongation

29

Chapter 5. Modeling

As mentioned in previous section, phenomena for all wires attached to the

index finger can be divided into two cases. In this section, model has been

presented for wire attachment to MCP joint flexion. Model for wire passing

Velcro strap is yet to be studied.

5.1 Model for Wire Attachment at MCP Joint

Figure 5.1 shows MCP joint wire attachment model for flexion. Four

linear springs are used to keep model simple. Each linear spring represents

the four major deformation factors presented in previous section. This model

was built based on three assumptions. First, friction is negligible. Second,

TA Support can move only in one direction. Third, Velcro straps are assumed

to be point contact.

Bones in palm and MCP joint link have been drawn in thick bold line.

is MCP joint angle, a is the distance from TA Support initial position to palm

Velcro strap projected to palm bone point, b is the distance between a and

MCP joint, c is the distance from MCP joint to wire attachment point, d is

the radius of MCP, e is the distance from initial palm Velcro strap position to

palm and f is the distance from TA Support wire position to Palm. to

30

represent spring constants for each spring and to represent spring

displacement. is TA Support movement, is palm Velcro strap

movement, is wire attachment point movement and is wire

elongation. Based on this model, actuated wire displacement can be

calculated. ∆ is actuated wire length, including actuation displacement

loss. T is the wire tension.

∆ , , , (5.1.1)

, (5.1.2)

, , , (5.1.3)

, (5.1.4)

. (5.1.5)

In these equations, a to f is constant and L and T are inputs. Spring

constants, to , are unknown and is the value that should be

predicted with inputs. Since equations related to are multivariate

nonlinear time invariant equations, to can only be estimated based on

fitting through experiment. For better estimation, ki should be nonlinear spring

constant. To have nonlinear springs for each deformation components, each

component will be function of MCP joint angle and wire tension. To estimate

nonlinear spring constant of this function, outrageous number of experiments

31

have to be conducted. However, since every single patient have different hand

parameter and stiffness, every patient will have different nonlinear spring

characteristics, which means great number of experiments has to be conducted

for each patients. Not only conducting experiments are hard, but also

estimating nonlinear spring constant is hard and expanding this model to other

finger joints is impossible.

Therefore, the deformation model presented in this paper will be using

linear spring constants and these spring constants will be estimated with only

one single case experiment result. Spring constants estimation will be

presented in following chapter.

5.2 Model for Force Estimation of MCP Joint

After estimating spring constants for each deformation components by

experiments, model for wire attachment at MCP joint has been completed.

Torque acting on MCP joint can be calculated based on tension acting on wire

between wire attachment point and palm Velcro strap. Normal distance

between this wire and MCP joint is defined as moment arm of MCP joint.

Since palm Velcro strap deforms as tension on wire increases, moment arm of

MCP joint also changes. Figure 5.2 illustrates defined parameters for force

estimation of MCP joint model. Following are equation of moment arm, MA,

32

and equation for MCP joint torque, ,

MA , (5.2.1)

τ MA ∙ T. (5.2.2)

Based on torque calculation, force at the end of MCP, F, can be estimated.

Define the length of MCP as r, which is moment arm to calculate force of

MCP. Then, following equation shows the force estimation of MCP,

F . (5.2.3)

Experiment to verify force estimation model has been conducted and

presented in chapter 7.

33

Figure 5.1 MCP joint wire attachment model for flexion

34

Figure 5.2 Model for force estimation of MCP joint

35

Chapter 6. Experiment

6.1 Experimental Setup

Figure 6.1 shows the schematic of experimental set up. Experiment has

been conducted to see the relation between the wire tension and actuated

wire length for fixed MCP angle . To maintain constant MCP angle while

actuating index finger, palm has been fixed to test bed. Five experiments

each for three different MCP angles have been conducted. While experiment

was running, wire tension and actuated wire length was recorded by

LabVIEW and two camcorders placed in two different angles were recording

the movement of different components of the robot for motion tracking.

Front view camcorder records the movement of TA Support and wire

attachment point, and upper view camcorder records the palm Velcro strap

movement. Data taken from motion tracking and LabVIEW were

synchronized with time.

6.2 Spring Constant Estimation

In figure 6.2, each line represents single experiment result and each color

represents 3 different MCP joint angles, which are 17˚, 22˚ and 31˚. For each

36

MCP joint angles, 5 experiments were conducted to show repeatability and

shown in figure 6.2. For each MCP joint angles, range of actuated wire

length was control parameter to have repeatable experimental result.

Actuated wire length was the control parameter in this experiment. Since the

wire tension was not the control parameter, in figure 6.2, maximum tension

for each MCP joint angle was different. In figure 6.2, all experiment result

shows that wire tension suddenly drops as soon as loosening the wire. The

main reason for this occurrence is the friction. The friction between the wire

and the sheath or the glove holds the wire at the moment when wire loosens.

Due to the effect, only wire tension drops first, while the length of the

actuated wire length is sustained. However, the data while pulling the wire is

only valuable, since the wire is for flexion actuation. Therefore, this paper

focuses only on wire pulling part of the data.

Dashed line in the figure 6.2 shows the relationship between the actuated

wire length and the tension when rigid model is used for MCP joint angle

17°. If conventional rigid model is used for soft exoskeleton, as soon as

MCP joint is fixed, actuated wire length will no longer increase and only

tension on wire will increase. However, due to the deformation of the robot,

especially glove, even after the MCP joint angle is fixed, actuated wire

length increases alongside the wire tension.

37

In figure 6.2, as MCP joint angle, , increases, initial actuation position of

wire also changes. Actuated wire length until wire tension increases

represents the wire needed to move from initial MCP joint angle zero to

target MCP joint angle. It is obvious that wire needed to move MCP joint

angle to target angle increases as target angle increases. While developing

model for MCP flexion, this should be also taken into account.

One big barrier of exoskeletons that encounter is physical size difference

of human body. Especially, hand size difference of each patient is critical

problem for soft exoskeleton for human hand. To overcome this barrier,

customizing soft exoskeleton to patient hand is necessary. This means all

parameters of the model will change for every single patient. Based on the

fact that the experiments are repeatable and have similar slope for different

MCP joint angles as shown in figure 6.2, the model will be using only one

experiment result to estimate spring constant. If the model can be completed

with only one experiment, patients don’t have to conduct so many

experiments for their own soft exoskeleton every time. Due to the reason,

spring constants have been estimated with single experiment.

Figure 6.3 shows the spring constant estimation for each deformation

factors for one experiment at MCP joint angle 17˚. Black dots are TA

Support movement, cyan dots are wire attachment point movement and

38

magenta dots are wire path change by palm pulley movement and these data

are taken from motion tracking. Green dots are wire elongation estimation

calculated by wire tensile test results. Colored line represents linear

estimation of each deformation factors and slope of the colored line

represent the spring constant estimation for each deformation factors. In the

figure 6.3, TA Support movement (black dot) and wire path change (magenta

dot) tends to follow each other closely. The reason for this is that TA Support

movement is more dominant factor in calculating wire path geometry change.

From figure 6.3, among all four deformation factors, each factor is equally

important in this model.

After calculating the wire path geometry change factor with TA Support

movement and palm Velcro strap movement with MCP joint angle 17˚, the

graph tends to follow linear spring motion. So to simplify the model,

complicated function for wire path geometry change has been remodeled to

another linear spring with spring constant k2’. Magenta line slope represents

k2’. Following equation shows the new model,

∆L x , (6.2.1)

x , , , . (6.2.2)

Figure 6.4 shows the result comparing the total actuated wire length, L,

39

from experiment and values calculated from the model. Blue dots represent

actual actuated wire length from the experiment and red dots represent the

total estimated wired length from model. Red dots represent the sum of four

different deformation factors, black, cyan, green and magenta shown in

figure 6.3. By the fact that red dots are following blue dots well, author

presume that modeling fits the actual system well.

Table 1 shows the result of spring estimation for each component, spring

constants. Units are in kgf/mm.

Current model (6.2.1, 6.2.2) and Table 1 shows complete model for single

experiment with MCP joint 17˚. However, this model does not count initial

actuation point change as MCP joint angle change as mentioned early in

this chapter. To add this factor, function of has been added to previous

model. For four initial actuation points, including zero position, quadratic

function has been used with least square method as shown in figure 6.5.

Following model is final model for all MCP joint angles,

∆L x , (6.2.3)

. (6.2.4)

Figure 6.6 shows the comparison between the experiment results and

estimation based on final model. Blue lines represent estimation based on

40

model for each MCP joint angle. Estimation by model follows the trend of

actual motion, but not very accurate. However, without deformation model

introduced in this paper, conventional rigid model has to be used and

estimation with rigid model is shown in colored vertical dashed lines.

Comparing deformation model with rigid model, deformation model give

much better estimation than rigid model. Previously, estimation with rigid

model had error that was too big to be compensated. On the other hand,

estimation with deformation model gives much less error, giving chance to

handle this error by control algorithm or by feedback with additional sensors,

which will give good possibility to control soft exoskeleton.

41

Table 6.1 Spring constant estimation result

k1 k2 k3 k4 ktotal

0.509 0.469 0.613 0.506 2.147

42

Figure 6.1 Schematic of experimental setup

Figure 6.2 Wire tension vs. Actuated wire length for different angles

43

Figure 6.3 Actuated wire length vs. wire tension for four factors of

deformation for MCP joint angle 17˚

0 0.5 1 1.5 2 2.5 3 3.50

1

2

3

4

5

6

7

8 = 17 deg

Wire Tension(kgf)

Wire

Len

gth(

mm

)

TA Support

Wire attachment pointWire elongation

Geometry change

44

Figure 6.4 Actuated wire length vs. wire tension: Comparison between

experimental result(blue dots) and modeling estimation(red dots)

0 0.5 1 1.5 2 2.5 3 3.50

5

10

15

20

25

30 = 17 deg

Wire Tension(kgf)

Wire

Len

gth(

mm

)

Experiment

Model EstimationEstimation Fitting

45

Figure 6.5 Initial actuation position estimation using Least Square

Method

46

Figure 6.6 Wire tension vs. actuated wire length: Comparison among

deformation model(blue solid line), rigid model(colored dotted line) and

experimental result(colored solid line)

47

Chapter 7. Posture and Force Estimation

To verify deformation model for MCP presented in this paper, posture

estimation for two cases and force estimation has been conducted and

compared with actual robot actuation. Same parameters and spring constants

were used as in previous chapter.

7.1 Posture Estimation

7.1.1 Constant Force Applied

From experimental setup in chapter 6, MCP joint fixation structure has

been removed. Since giving constant force to MCP joint while MCP joint is

moving is impossible, author intentionally gave constant force on finger.

While conducting experiment, motion tracking has been used to measure

actual MCP joint angle while actuation. Also, tension and actuated wire

length has been recorded to estimate MCP joint angle by deformation model

presented in this paper. Since the final model is composed of wire tension,

actuated wire length and MCP joint angle, calculating MCP joint angle

by two other factors is easy.

Figure 7.1 shows the comparison result between actual measured MCP

48

joint angle and estimation of MCP joint angle by final deformation angle.

Dots shows the posture estimation of MCP joint angle by deformation model

and crosses shows the measured MCP joint angle. As presented in figure 7.1,

deformation model cannot detect where MCP joint angle is initially at.

Deformation model assumes that MCP joint angle is initially at 0˚, while

actual MCP joint was at around 28˚. As soon as actuation starts, wire is

pulled without tension until wire reach initial position of wire for MCP joint

angle 28˚. Around this position, tension starts to increase and posture

estimation tends to follow the actual MCP joint angle. There exists error

between estimation and experiment result, which is less than 10˚. Author

presumes that this error can be handled by control or by additional feedback

system.

7.1.2 Random Force Applied

Same experimental setup to previous posture estimation experiment has

been used. Instead of constant force on MCP joint as in previous experiment,

random force has been applied to MCP joint to explicitly see how well the

deformation model can follow actual MCP joint angle.

Figure 7.2 shows the comparison result between actual measured MCP joint

angle and estimation of MCP joint angle by final deformation angle. Dots

49

shows the posture estimation of MCP joint angle by deformation model and

crosses shows the measured MCP joint angle. Also, in this experiment, author

can see that deformation model catch up with actual MCP initial position and

tend to follow the MCP joint movement with error less than 10˚.

Using rigid model, it is impossible to estimate the posture of MCP joint

with wire tension and actuated wire length.

7.2 Force Estimation

Instead of MCP joint fixation structure in experimental setup, two load cells

combined to measure force in x-y plane has been placed. These load cells are

placed right before PIP joint, where MCP joint angle is placed. This

experiment has been conducted with MCP joint angle 25˚. As mentioned in

chapter 5.2, force estimation model has been built based on final deformation

model. Crosses in figure 7.2 show actual force of MCP measured by load cells.

Dots are estimation by force estimation model. The reason for measured value

is not starting from zero is that experiment has been conducted initially with

MCP contact to load cell. Due to the passive stiffness of the finger joint, initial

measured value of load cell is not zero. Around four seconds, wire actuation

starts and force estimation values tend to follow experimental result well.

This experiment result of force estimation model is closer to experimental

50

result than deformation model. The reason is only palm Velcro strap

movement is the deformation factor, variable, in force estimation model.

Since force estimation model only involves one deformation factor, this gives

higher precision than deformation model.

51

Figure 7.1 MCP joint angle comparison between experimental result

and posture estimation by deformation model: Constant force applied

52

Figure 7.2 MCP joint angle comparison between experimental result

and posture estimation by deformation model: Random force applied

53

Figure 7.3 Comparison between experimental result and MCP force

estimation at MCP joint angle 25˚

54

Chapter 8. Conclusion

This paper presented two successful approaches to increase controllability

of soft wearable robotic hand. One is by minimizing the nonlinearity factors

of the system through improving the component of the robot physically,

which is development of TA Support. TA Support not only is to decrease the

nonlinearity of the system, but also is necessarily needed to transmit force

from motor to the fingertip. The other is to model deformation factors of the

system, which is MCP joint flexion model.

Main function of TA Support is to transmit the wire tension to the finger

link. Since TA Support and motor system frame is one body, force

transmission to target point occurs as soon as TA Support is fixed to the hand.

Therefore, TA Support was developed based on several design considerations,

especially customizing. Customizing TA Support fulfilled two important

features, fixation and pressure distribution. Customizing is important because

of difference in every patient’s hand. Hence, fabrication process has been

established to easily customize TA Support and stated. Development of

customized TA Support has drastically increased the fixation to the hand, but

still TA Support cannot be fixed to the hand perfectly due to the compliance

of skin and small gap between the TA Support and hand.

55

Modeling for MCP joint flexion in soft exoskeleton for index finger was

built as part of to control fingertip force and force direction. To control

fingertip force and direction, this current MCP flexion model has to be

extended to PIP joint and DIP joint. Also, as stated in the body, model for

Velcro strap movement has to be built to fully control fingertip force and

direction. Even if, only the modeling for MCP joint flexion was built, this

shows good prospective view to control the soft exoskeleton. In any

developing tendon driven soft exoskeleton, engineers will meet serious

control issues due to the nonlinearity caused by deformations and frictions

occurring on several parts of the robot. Once the modeling for whole index

finger is built, this will give good prospective view in soft exoskeleton

modeling.

56

Bibliography

[1] Y. Kadowaki, T. Noritsugu, M. Takaiwa, D. Sasaki and M. Kato,

“Development of Soft Power-Assist Glove and Control Based on

Human Intent,” Journal of Robotics and Mechatronics, Vol. 23,

pp.281-291, 2011.

[2] E.B. Brokaw, I. Black, R.J. Holly and P.S. Lum, “Hand Spring

Operated Movement Enhancer (HandSOME): A Portable, Passive

Hand Exoskeleton for Stroke Rehabilitation,” IEEE Transactions

on Neural Systems and Rehabilitation Engineering, Vol. 19, No. 4,

pp. 391-399, 2011.

[3] T. Kline, D. Kamper, and B. Schmit, “Control System for

Pneumatically Controlled Glove to Assist in Grasp Activities,”

International Conference on Rehabilitation Robotics, pp. 78-81,

2005.

[4] D. Sasaki, T. Noritsugu, M. Takaiwa, H. Yamamoto, “Wearable

power assist device for hand grasping using pneumatic artificial

rubber muscle”, IEEE International Workshop on Robot and

Human Interactive Communication, pp. 655- 660, 2004.

[5] S. Mohamaddan and T. Komeda, “Wire-driven mechanism for

finger rehabilitation device,” International Conference in

57

Mechatronics and Automation, pp. 1015-1018, 2010.

[6] H. In, K. Cho, K. Kim, B. Lee, “Jointless structure and under-

actuation mechanism for compact hand exoskeleton”, IEEE

International Conference on Rehabilitation Robotics, pp. 1-6, 2011.

[7] H. In and K. Cho, "Compact Hand Exoskeleton Robot for the

Disabled", The 6th International Conference on Ubiquitous Robots

and Ambient Intelligence, pp.86-89, 2009.

[8] B.B. Kang, H. In, K. Cho, “Force transmission in joint-less tendon

driven wearable robotic hand”, International Conference on

Control, Automation and Systems, pp. 1853-1858, 2012

[9] M. Fontana, A. Dettori, F. Salsedo, and M. Bergamasco,

“Mechanical design of a novel Hand Exoskeleton for accurate

force displaying,” IEEE International Conference on Robotics and

Automation, pp. 1704-1709, 2009.

[10] Y. Hasegawa, Y. Mikami, K. Watanabe, Z. Firouzimehr, and Y.

Sankai, “Wearable handling support system for paralyzed patient,”

IEEE International Conference on Intelligent Robots and Systems,

pp. 741-746, 2008.

[11] A. Wege and A. Zimmermann, “Electromyography sensor based

control for a hand exoskeleton,” IEEE International Conference on

58

Robotics and Biomimetics, pp. 1470-1475, 2007.

[12] B. L. Shields, J. A. Main, S. W. Peterson and A. M. Strauss,“An

anthropomorphic hand exoskeleton to prevent astronaut hand

fatigue during extravehicular activities,” IEEE Transactions on

Systems, Man and Cybernetics, Part A: Systems and Humans, Vol.

27, No. 5, pp. 668-673, 1997.

[13] S. Ueki, H. Kawasaki, S. Ito, Y. Nishimoto, M. Abe, T. Aoki, Y.

Ishigure, T. Ojika and T. Mouri, “Development of a Hand-Assist

Robot With Multi-Degrees-of-Freedom for Rehabilitation

Therapy,” IEEE Transactions on Mechatronics, Vol. 17, No. 1, pp.

136-146, 2012.

[14] M. DiCicco, L. Lucas and Y. Matsuoka, “Comparison of control

strategies for an EMG controlled orthotic exoskeleton for the hand,”

IEEE International Conference on Robotics and Automation, Vol.

2, pp. 1622-1627, 2004.

[15] K. Tadano, M. Akai, K. Kadota and K. Kawashima, “Development

of grip amplified glove using bi-articular mechanism with

pneumatic artificial rubber muscle,” IEEE International

Conference on Robotics and Automation, pp. 2363-2368, 2010.

[16] K. Toya, T. Miyagawa and Y. Kubota, “Power-Assist Glove

59

Operated by Predicting the grasping Mode,” Journal of System

Design and Dynamics, Vol. 5, No. 1, pp. 94-108, 2011.

[17] S. Moromugi, K. Kawakami, K. Nakamura, T. Sakamoto, and T.

Ishimatsu, “A tendon-driven glove to restore finger function for

disabled,” ICROS-SICE International Joint Conference,

Proceedings, pp. 794–797, 2009.

[18] S. Mustafa, S. Agrawal, “On the force-closure analysis of n-DOF

cable-driven open chains based on reciprocal screw theory”, IEEE

Transactions on Robotics, Vol. 28, No. 1, pp.22-31, 2012

60

초 록

본 논문은 텐던 드리븐 메커니즘을 이용한 유연한 입는형 손가락

로봇의 제어능력을 향상시키기 위해 두 가지 방법을 제안한다. 텐던

엥커링 서포트는 모터의 힘을 와이어를 통해 원하는 구동 지점까지

전달하기 위한 파트로서 손에 고정이 잘 되어야 하는 특성을

가지도록 개발되었다. 텐던 엥커링 서포트는 손에 고정이 잘 되기

위하여 환자마다 손의 모양이 다른 것을 감안해 맞춤형으로 제작이

되었다. 이 파트를 간편하게 맞춤형으로 제작하기 위하여

공정과정이 개발이 되었다.

또한 본 논문에서 손가락의 각도를 추정하기 위한 장갑 변형

모델과 힘 추정 모델을 소개한다. 유연한 입는형 손가락 로봇의

손가락 끝 단의 힘을 제어하기 위한 모델을 만드는 첫 번째

과정으로 중수지절관절 장갑 변형 모델이 만들어졌다. 이 모델은

실험을 통하여 완성이 되었고, 이 모델을 바탕으로 중수지절관절 힘

추정 모델을 만들었다. 이 두 모델의 정당성은 실험을 통해

입증되었다.

텐던 드리븐 메커니즘을 이용한 유연한 입는형 로봇을 만드는

공학자라면 누구나 로봇의 제어에 관한 문제에 당면하게 된다. 이

61

논문에서 소개한 모델들은 이러한 문제를 해결하는데 좋은

방향성을 제시할 것이다.

주요어: 유연한 입는형 로봇 모델, SNU Exo-Glove, 텐던 엥커링

서포트, 중수지절관절 모델, 중수지절관절 각도 추정, 중수지절관절

힘 추정

학 번: 2011-20680