Reduced DoFs of Digital Hand Based on Anatomy

for Real Time Operation

Hiroshi Hashimoto

, Akinori Sasaki

, Koji Makino

and Kaoru Mitsuhashi

Advanced Institute of Industrial Technology, Shinagawa-ku, Tokyo, Japan

Tokyo Metropolitan Industrial Technology Research Institute, Koto-ku, Tokyo, Japan

University of Yamanashi, Kofu-shi, Yamanashi, Japan

Tokyo University of Technology, Hachioji-shi, Tokyo, Japan

Keywords:

Digital Hand, Reduced DoFs, Hand Anatomy, Real Time Operation.

Abstract:

This paper describes a model of using a digital hand, which mimics human hands, operates dynamically in real

time operation. Focusing on real time operation, we consider a model structure of digital hand with reduced

DoFs (degree of freedoms) as an approximated model, where the reduction is based on the anatomical and

medical hand analysis. There some problems because of the approximated model. To overcome the problems,

some techniques are implemented into the model. We examine how the model is able to mimic the movement

of human hands.

1 INTRODUCTION

This paper describes a model of using a digital hand,

which mimics human hands, operates dynamically in

real time operation. Focusing on real time operation,

we consider a model structure of digital hand with re-

duced DoFs (degree of freedoms) as an approximated

model, where the reduction is based on the anatom-

ical and medical hand analysis. We examine how

the model is able to mimic the movement of human

hands.

Many signiﬁcant works on digital hand have

been studied very well in the ﬁelds of robot

hands, ergonomics on grasping objects, animation

and so on(H.Kawasaki and K.Uchiyama, 2002),(Tet-

suyou Watanabe and Jiang, 2006). The objective

of the robot hand study has different view point

from the structure of a human hand, because it it to

grasp an object in stable situation (Nguyen, 1986),

(T.Yoshikawa, 1996). In the animation, consider-

ing muscular, freedom of joints or tendons, a pre-

cise digital hand to mimic human hand is tried to

be made(J.Lee and T.Kunii, 1995),(Shinjiro Sueda

and Pai, 2003),(S.Mulatto and D.Prattichizzo, 2013),

(Yui Endo and Shimokawa, 2002). Its objective is

to evaluate product designs when it grasp an object.

To do this, the discussions are made about parameter

identiﬁcations of the digital hand, and grasping situ-

ation on contact points between the digital hand and

object. These considerations focus on the static states

while grasping statically, not dynamical states such as

pen spinning.

On the other hand, the human hand is able to ma-

nipulate objects dexterously. For example, the human

hand can pass an instrument from appropriate ﬁngers

to the other with only ﬁnger. Further, pen spinning

operations give a much value as theater. These op-

erations lead to a rapid use of the instrument or cre-

ate much valuable things. The dynamical operation

of the digital hand has been slightly considered in

(H.Hashimoto and C.Ishii, 2013), (H.Hashimoto and

Y.Ohyama, 2014), not seen in the other study. In the

previous research, the body of the digital hand was

made from rigid body.

Human hand is covered by soft skin, whichi is de-

formable while operating an object. Therefore, con-

tact region touched with the object is area not point for

rigid skin, so the dynamic relationship on the contact

region also becomes complex. This means the real

time operation of the digital hand requires numerous

computational load.

Because the way of moving of is very enormous

to operate a thing dynamically, it will program it ev-

ery judging from the existing state of things to make

the manual based on the program and is very trouble-

some. Manipulating the digital hand dynamically, it

is too numerous paterns that its posture shows to real-

764

Hashimoto H., Sasaki A., Makino K. and Mitsuhashi K..

Reduced DoFs of Digital Hand Based on Anatomy for Real Time Operation.

DOI: 10.5220/0005099807640768

In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO-2014), pages 764-768

ISBN: 978-989-758-039-0

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

ize it for various operation cases.

To overcome the problems such as the computa-

tional load with soft skin and real time operation for

various operation cases, ﬁrst, we propose a digital

hand structure with reduced DoFs of joints based on

anatomy. Second, the operation system with hand-

posture sensor (LeapMotion, 2014) and virtual phys-

ical space which is realized with Bullet Physics (Bul-

letPhysics, 2014). To conﬁrm the effectiveness of the

digita hand system, some operations are examined.

2 HUMAN HAND KINEMATICS

MODELING

Based on anatomical and medical hand analysis of

previous studies and research, the hand skeleton

model has 23 internal DoFs (Figure 1) (Kapandj,

2008),(Zatsiorsky, 1998).

Thumb

Index

Middle

Ring

Little

carpals

DIP

PIP

MCP

CMC

Wrist

TMC

Figure 1: Hnad skelton structure.

Next, let us consider to reduce the DoFs to reach

real-time operation with our system. Here, the dex-

terous pose and motion of hand should be kept in

good condition such as the arches(N.Kamakura and

Y.Miura, 1980),(S.J.Edwards, 2002). So, the DoFs of

thumb needs to consider very carefully. The range of

deviation of MCP joint of the thumb is so small for

abduction/adduction that it can be usually neglected,

and its DoFs can be approximated as one.

Not to force the action of bending the ﬁngers, but

to act for ﬂexion/extension, there is an angular con-

straint condition between the angle of DIP and of PIP

for each ﬁnger such as (E.Y.Chao and R.L.Linscheid,

1989), (Y.Wu and T.S.Huang, 2005).

angle(DIP) = α angle(PIP) (1)

where angle ( joint ) means the angle of joint and

α ≃

(2)

From the fact, the angles of DIP and PIP are linearly

independent, so one DoF for each ﬁnger can be re-

duced. Figure 2 shows the structures of the skeleton

model under the consideration described above. As

shown in Figure 2, the DoFs of four ﬁngers is nnn

each, the DoFs of thumb is mmm, and the total DoFs

is llll, which attain to reduce iiiii from the original

DoFs.

Thumb

Index

Middle

Ring

Little

Figure 2: Structure model of joints and bones.

The model in Figure 1 is based on the anatomy.

The DoFs will become more reduced to be suitable

the input device described later.

3 STRUCTURE OF DIGITAL

HAND

Human hands consist of rigid bone and soft skin

which forms deformable surface when hand grasping

objects. The rigid bone support to pick at a small ob-

ject and the soft skin is to prevent to drop an object

with friction on the contact area between deformable

skin and the object. Therefore, a complex operation

of human hand is realized. First, the design of the soft

skin is described, then the its connection with rigid

bone is shown.

3.1 Design of Soft Skin

In making the digital hand by using Bullet Physics

as a physics engine, it is difﬁcult to join soft skins

ReducedDoFsofDigitalHandBasedonAnatomyforRealTimeOperation

765

to rigid bones. This is because the schemes of those

collision detections are different.

From this, we think about only skin of the size that

only comes in contact with the object. And the con-

nection between the soft skin and the rigid bone uses

an anchor combination of Bullet Physics, not direct

combination. For this reason, the skin is designed to

be able to installed onto the tip of the ﬁnger and the

middle of each bone. The shape of the skin of ﬁn-

gertip is made by Blender (Blender, 2014) shown in

Figure 3.

Figure 3: Making of Soft Skin in Blender window.

The number of mesh that make up part of the

hemisphere ﬁnger tip and the ﬁnger pulp is too large,

the calculation time required for collision detection is

enormous, and it can not achieve real-time operation.

Based on the trade-off of computational load and fea-

sibility of the dexterous hand operation, the selection

of the number is determined by trial and error.

Next, the ﬁgure of the soft skin is introduced into

soft body of Bullet Physics, and some parameters (Ta-

ble 1) of soft body should be deﬁned to set up it.

However, the effective way to identify them have

not shown yet, so we investigated that human hand

played the bar spinning as a manipulation with the

high-speed camera (1000 fps ) as shown in Fig. 4.

Investigating the deformable skin from it, the param-

eters are adjusted to show the same deformable soft

skin.

Figure 4: Scene of bar spinning.

Table 1: Parameters of soft body in Bullet Physics.

kDP Damping coefﬁcient; damps forces

acting on soft body nodes to reduce

their oscillation over time. Imagine

a mass hanging on a spring. Range

[0,1]

kDG and

kLF

Drag and Lift coefﬁcient; relat-

ing to aerodynamics (see wikipedia

pages for ”drag coefﬁcient” and ”lift

(force)”). Range [0,+∞]

kDF Dynamic friction coefﬁcient; just

friction of nodes against surfaces, as

with rigid bodies. Range [0,1]

kMT Pose matching coefﬁcient; be used

with setPose(bool, bool). Range

[0,1]

kCHR,

kKHR

and

kSHR

Rigid, kinectic and Soft contacts

hardness; controling how strict any

overlap between the soft body and

other types is treated. Range[0,1]

3.2 Combination of Skin and Bone

The bong is made from a cylinder rigid body and uses

a motor as rotating joints, The DoFs is in accordance

with the joint of the hand described the previous sec-

tion. When the skin is connected with the bone, the

gap of the joint is sufﬁcient distance movable range of

each joint to be achieved.

Figure 5 shows one ﬁnger conducted by the design

described above.

Figure 5: Digital ﬁnger with soft skin and rigid bone.

In Figure 5, the rigid bone and the soft skin are

connected with anchors. Each anchor has a motor to

rotate the joint, and it is controllable to appropriate

reference angle or velocity.

Figure 6 shows the extending this conﬁguration to

the ﬁve ﬁngers.

For through hand operation in real time, and is

focused on seeing the mechanical interaction of the

ICINCO2014-11thInternationalConferenceonInformaticsinControl,AutomationandRobotics

766

Figure 6: Digital hand.

hand and the object, this paper will not be rendered.

Because we focus on operating the digital hand in

real time and investigating the dynamical interaction

with the object, the rendering of CG is not introduced.

3.3 Virtual Physical Space

Our digital hand is able to grasp and manipulte ob-

jects in the Virtual Physical Space. In the develop-

ment with Bullet Physics, the space would be not well

deﬁned yet. So, we deﬁne it such that the Virtual

Physical Space is the three-dimensional extent shown

in the computer simulation, in which an approximate

simulation of certain physical systems, such as rigid

body dynamics (including collision detection), soft

body dynamics is provided by a proper physics en-

gine.

The digital hand and appropriate objects are set

in the Virtual Physical Space, then gravity, collision

detection and rotation calculations for them are cal-

culated. So, in the space the digital hand is able to

grasp or manipulate the object.

4 REAL TIME OPERATION

SYSTEM

4.1 Hand Posture Sensing

In this study, the Leap Motion Controller (LMC) is

introduced as a hand posture sensing device (Leap-

Motion, 2014), (LeapMotionSDK, 2014).

The LMC is able to detect some informations of

ﬁnger such that the position of ﬁnger tips and the di-

rection vector of ﬁngers, but not the joint angles of the

ﬁnger. As informations of the palm, the LMC is able

to detect the normal vector to the palm. If the hand is

ﬂat, the vector will point downward. When the hand

becomes grasping posture, then the shape of parm is

assumed to be arch and the virtual sphere is placed as

if the hand were holding a ball by posturing the arch.

Then, the center position of the sphere is detected.

From the hand informations described above, the

posture of hand is able to estimated what are open,

holding and arch (LeapMotionSDK, 2014). In those

posture, we use the approximated posture whose

joints are linearly dependent such as

angle(MCP) = β angle(DIP) (3)

and

angle(CMC) = γ direction(DIP) (4)

for holding. Where direction( ﬁnger) means the abso-

lute of the direction vector of the ﬁnger, β and γ are

deﬁned from the examination of hand operating.

4.2 Implementation

A demonstrative application was developed to evalu-

ate the digital hand in operation by the postures. The

goal is to set up the digital hand in real time opera-

tion. The software application is executable on the

CPU(Core i7-4900MQ, 2.8GHz) and the GPU(Nvidia

Quadro K4100M, 1152 Cuda processors). In our

goal, the roles of CPU and GPU are assigned sepa-

rately as following

• Finger Callback : CPU

• Graphics Thread : GPU

• Physics Simulation : GPU

These processing assigned to CPU and GPU is enable

to use PyCUDA(PyCUDA, 2014), the assigned has

been developing in the present circumstances.

4.3 Experiment

The operator is operate the digital hand in real

time,using the Leap Motion as the input device of the

human hand posture as shown in Figure 7 According

Leap Motion Controller

Figure 7: Digital hand system with input device Leap Mo-

tion.

to the movement of human ﬁgures and palm of the

ReducedDoFsofDigitalHandBasedonAnatomyforRealTimeOperation

767

hand, the digital hand change its posture to mimic the

hand in real time. And when the digital hand grasp an

object in the virtual physic space, the collision detec-

tion between the digital hand and the object is trans-

mitted to the physics engine, and the digital hand can

grasp it according to the varying hand posture in real

time.

5 CONCLUSIOIN

This paper proposed a novel design procedure of the

digital hand, which is in reduced DoFs, the design of

soft skin, rigid body and those connection approach,

and real time operation system.

The reduced DoFs of the digital hand is proposed

by considering anatomy, which is to be operated in

real time. The total number of reduced DoFs is 16,

which is less than six degrees of actual DoFs.

The design of soft skin and rigid body is regular

way in CG creation, but the connection approach is

devised because the collision detection of each body

shows different phases. This approach relates on the

shape of the soft skin.

The real time operation is considered about the

digital hand with reduced DoFs and the usage of the

LMC. To use the cheaper devices will expand our sys-

tem to ordinary users. So, we have been develop-

ing the real time operation system, and the applicable

demostration to show the real time operation will be

shown.

ACKNOWLEDGEMENTS

This work was supported by JSPS KAKENHI Gran

Numbers 25280125, 25560009 and in part supported

by JST RISTEX Service Science, Solutions and

Foundation Integrated Research Program.

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