Reduced DoFs of Digital Hand Based on Anatomy
for Real Time Operation
Hiroshi Hashimoto
1
, Akinori Sasaki
2
, Koji Makino
3
and Kaoru Mitsuhashi
4
1
Advanced Institute of Industrial Technology, Shinagawa-ku, Tokyo, Japan
2
Tokyo Metropolitan Industrial Technology Research Institute, Koto-ku, Tokyo, Japan
3
University of Yamanashi, Kofu-shi, Yamanashi, Japan
4
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
Copyright
c
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
dp
mp
pp
mc
carpals
DIP
PIP
MCP
IP
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
3
(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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