Human body dynamics

jadesoreΤεχνίτη Νοημοσύνη και Ρομποτική

13 Νοε 2013 (πριν από 3 χρόνια και 4 μήνες)

67 εμφανίσεις



:外界センサー

人間


モーションキャプチャ:


運動データ


床半力


外力


逆運動学計算





:外界センサー

人間


動作画像

モーションキャプチャー

モーションキャプチャー

逆運動学

逆力学



:外界センサー

人間


15
リンク

[Nakamura et al. 2000]

,
[Venture et al. 2008]


34
自由度
(DOF)


マーカーから逆運動学計算


関節角度、速度、加速度

[Yamane
et al. 2003]



:外界センサー

人間
モデリング・最少パラメータ


Standard parameters = full set of inertial parameters




Base parameters = identifiable parameters from
inverse dynamics only (
Y
B

of full rank)

15

同定のため適当な動作は?







リグレサーの状件数

Cross Validation






:外界センサー

人間

RT
同定


モーションキャプチャ

(motion analysis)


床半力

(Kistler)



Screen for visual
feedback


PC for motion
acquisition


PC for real
-
time
computation




:外界センサー

人間

RT
同定


From motion capture
(RT IK computations)


and force
-
plates
(RT generalized effort computations)



base and SP are identified with RT method
(recursive algorithm)

Geometric scaling and initial SP


Measure the geometric parameters of the
model from motion capture: automatic
scaling from marker positions


Estimate the initial SP
f

ref

from geometric
parameters and database of human body.

Initial geometric parameters and
SP identification for 3 candidates
with 3 different morphologies:
1.73m 58Kg, 1.62m 54Kg and

1.76m 76.3Kg

Persistent Exciting trajectories


Using RT color changes to specify the links
not yet completely identified, results are
obtained in a shorter time with more
accuracy.


Persistent Exciting trajectories

3.
Real time identification of the human dynamics

同定結果


Comparison of some identified parameters
with literature
[Young et al. 1983]

応用:スポーツトレーニング


33 year old female


Stanton marathon training program in preparation
for the 2009 Tokyo Marathon.


Training program = 16 week program


5
-
days a week running schedule


Gradually increased running distance from 20km/week to
80km/week in the peak 13th week, then tapering in the
final 3 weeks before the race.


Prior to that subject runs 25km/week


Record on a weekly basis / several sessions omitted

応用:スポーツトレーニング

例4:関節粘弾性の同定


Biomechanics developed methodologies for
measuring various dynamics properties of the
human body


Determination of standard values of joints’
visco
-
elastic
properties based on well calibrated measuring equipments
and averaging of data of many subjects.


Equipment need mechanical stiffness and accuracy



heaviness and bulkiness (dynamometer)



not applicable to everyone, specially to people under
rehabilitation and medical treatments.




System to measure patient
-
specific
visco
-
elastic
properties of limb joints without pain and constraints
highly required.

例4:関節粘弾性の同定


Joint
modelling


Model of
visco
-
elastic
properties adapted
from biomechanics
most popular model

+Identification of human joint passive dynamics, Proc. of the IEEE Int. Conf. on Robotics and Automation, pp
2960
-
2965, 2006.

+Identification of Human Limb
Visco
-
Elasticity Using Robotics Methods to Support the Diagnosis of Neuromuscular
Diseases, Int. J. of Robotic Research (to be
publiched
)

神経病の診断

21

実験結果


Possible discrimination of patients

終わり


参考論文


W. Khalil and E. Dombre.
Modeling, identification and control

of robots. Hermès Penton, London
-
U.K, 2002.


Y. Nakamura,
Advanced Robotics: Redundancy and Optimization,

Addison
-
Wesley Longman Publishing Co., Inc,
1990.




G. Venture, K. Ayusawa, and Y. Nakamura, “Motion capture based

identification of human inertial parameters,” in
Proc. IEEE/EMBS Int.

Conf. on Eng. in Medicine and Biology, 2008, pp. 4575

4578.


G. Venture, K. Ayusawa, and Y. Nakamura, “Dynamics identification

of humanoid systems,” in
Proc. CISM
-
IFToMM
Symp. on Robot

Design, Dynamics, and Control (ROMANSY), 2008, pp. 301

308.


Y. Fujimoto, S. Obata, and A. Kawamura, “Robust biped walking with

active interaction control between foot and
ground,” in
Proc. of the

IEEE Int. Conf. on Robotics and Automation, 1998, p. 2030˝U2035.


K. Yoshida, D.N. Nenchev, and M. Uchiyama, “Moving base robotics

and reaction management control,” in
Proc. of
the Seventh Int. Symp.

of Robotics Research, 1995, p. 100˝U109.


H. Mayeda, K. Osuka, and A. Kangawa, “A new identification method

for serial manipulator arms,” in
Proc. IFAC 9th
World Congress, 1984,

pp. 2429

2434.


C.G. Atkeson, C.H. An, and J.M. Hollerbach, “Estimation of inertial

parameters of manipulator loads and lunks,”
Int. J.
of Robotic

Research, vol. 5, no. 3, pp. 101

119, 1986.


H. Kawasaki, Y. Beniya, and K. Kanzaki, “Minimum dynamics

parameters of tree structure robot models,” in
Int. Conf. of
Industrial

Electronics, Control and Instrumentation, 1991, vol. 2, pp. 1100

1105.


W. Khalil and F. Bennis, “Symbolic calculation of the base inertial

parameters of closed
-
loop robots,”
Int. J. of Robotics
Research, vol.

14(2), pp. 112

128, April 1995.


M. Gautier, “Numerical calculation of the base inertial parameters,”

J. of Robotic Systems, vol. 8(4), pp. 485

506, 1991.


K. Ayusawa, G. Venture, and Y. Nakamura, “Inertial parameters

identifiability of humanoid robot based on the
baselink equation of

motion,”
Proc. of the Conf. on Robotics and Mechatronics, 2P1
-
F09,

2008, (in Japanese).