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Bum-Joo Lee, Yong-Duk Kim and Jong-Hwan Kim Robot Intelligence Technology Lab. KAIST. 16 th IFAC, Jul., 8, 2005. Balance control of humanoid robot for Hurosot. Contents. Introduction Gait generation First phase: walking pattern generation Second phase: yawing moment cancellation - PowerPoint PPT Presentation
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Robot Intelligence Technology Lab.
Balance control of humanoid robot for Hurosot
Balance control of humanoid robot for Hurosot
Bum-Joo Lee, Yong-Duk Kim and Jong-Hwan Kim
Robot Intelligence Technology Lab.
KAIST
16th IFAC, Jul., 8, 2005
Robot Intelligence Technology Lab. 2
Contents
Introduction
Gait generation
First phase: walking pattern generation
Second phase: yawing moment cancellation
Balance control
Inverted pendulum model
Compensation method
Experiment
Conclusions
Robot Intelligence Technology Lab. 3
1. Introduction
Humanoid robot
Biped (two-legged) robot. Expected to eventually evolve into one with a human-like body and intelli
gence.
HanSaRam Meaning ‘one human being’ in Korean A humanoid robot undergoing continual design and development in the R
obot Intelligence Technology Laboratory at KAIST since 2000
Stability ZMP (Zero Moment Point) must always reside in the convex hull of all
contact points on the ground plane. ZMP: the point on the ground plane at which the total moments due to gr
ound contacts becomes zero, proposed by Vukobratovic
Robot Intelligence Technology Lab. 4
HSR-I, II: 2000- Easy to make and control, Lack of torque
HSR-III: 2001- 12 DC motors and 10 RC servo motors - Human-like body- No sensor feedback
HSR-IV: 2002- 12 RC servo motors - Feedback using force sensors- No upper body
HSR-V: 2003- 12 DC motors and 16 RC servo motors - Feedback using force sensors- Human-like body
HSR-VI: 2004- 12 DC motors and 13 RC servo motors - Feedback using force sensors- Improved performance
HSR-I
HSR-II
HSR-III
HSR-IV
HSR-V
HSR-VI
1. Introduction
Robot Intelligence Technology Lab. 5
1. Introduction
Robot Intelligence Technology Lab. 6
Robot (HSR-V)ZMP
Compensator
Two Phase Off-line Gait Generator
< Off-Line >
< On-Line >
ZMP Calculator
Step Time,Step Size,
Maximum Foot Height Gait Generation Using Simulator
1st Phase
Yawing Moment Cancellation
Trajectory
Compensated Reference Joint Angle
Real Joint Angle Feedback
Sensor DataMeasured ZMP Data
Reference Joint Angle
2nd Phase
2. Two Phase Off-line Gait Generation
Control architectureControl architecture
Robot Intelligence Technology Lab. 7
))(),(( tztxPosture vector
Hiptrajectory
Foottrajectory
zmax
xmax
Ls
xsd
xed
Hmin
Hmax
Y
Z
RL
RL
RL
RL
RL
LL
LL
LL
LL
LL
LL
LL
LL
LL
LL
3*Ls
2*Ls
2*Ls
Ls
Ls
2. Two Phase Off-line Gait Generation
First phase: walking pattern generation First phase: walking pattern generation
Robot Intelligence Technology Lab. 8
sss
dss
ssfbsas
m
deffea
TTtL
TTtL
TtLLL
Ttx
TtLL
t
tx
2
2
))cos(1()sin(2
))cos(1()sin(
00
)( max
a
a
easfb
eaeff
a
L
L
LL
H
LL
L
tz)cos()sin(
)cos()sin(
)( max
LffLfb
La
2*Ls
Hmaxse
xmax x
Z
Gait generation (Huang 2000)Gait generation (Huang 2000)
1) Foot trajectory
2. Two Phase Off-line Gait Generation
Robot Intelligence Technology Lab. 9
2. Two Phase Off-line Gait Generation
ssds
ms
deds
sd
TtxL
TtL
TtxL
tx
tx
0
)(
s
m
d
TtH
TtH
TtH
tH
tz
min
max
min
min 0
)(
Xsd
Xed
z
x
Xsd
2) Hip trajectory
Robot Intelligence Technology Lab. 10
Interpolate at
Match velocity and acceleration values at every via points.
Calculate the trajectories of ankle and hip joints.
3rd order spline interpolation3rd order spline interpolation
)()()()( 32jjjjjjjj ttdttcttbats ],[ 1jj tt
2. Two Phase Off-line Gait Generation
Robot Intelligence Technology Lab. 11
2. Two Phase Off-line Gait Generation
Z
Y
Xn
ipii
n
i
i
i
i
pii
n
ipii
n
iipii
T
T
T
g
rrm
z
y
x
rrm
TGrrmrrrm
0
0
)(
)(
TermMoment Yawing :
)(
})({
)(
})({
n
iiZMPiiZMPiiZ
ii
iiiiiiZMP
ii
iiiiiiZMP
xyyyxxmT
gzm
yzmygzmy
gzm
xzmxgzmx
0 YX TT
ZMP equation:
Second phase: yawing moment compensationSecond phase: yawing moment compensation
Robot Intelligence Technology Lab. 12
2. Two Phase Off-line Gait Generation
XTrajectory of arm- COG
< Real arm model > < Simplified arm model >
yx
X
Z
o Y
Z
o
< Sagittal plane > < Frontal plane >
o
Z
Robot Intelligence Technology Lab. 13
2. Two Phase Off-line Gait Generation
0
2
12
0
,
xymM
xym
xyyyxxm
xyxyyyxyxxm
xyyyxxmT
a
a
n
iiZMPiiZMPii
aZMPaaZMPaa
n
aaiiZMPiiZMPiiZ
rl
ym
Mx
a 0
C.O.G. arm to origin coordinate local fromnt displaceme : , yx
Off-line yawing moment cancellation:
Above equation can be solved by numerical double integration.
Robot Intelligence Technology Lab. 14
3. On-line Balance control
< Simplified upper body model >v
Y
AlAl ML ,
AuAu ML ,
TT ML ,
SlSl ML ,
X
YZ
o
Z
o X
Y
UU ML ,
X
YZ
o
Z
o
Inverted Pendulum Model
< Lumped upper body model >
Robot modeling for online compensationRobot modeling for online compensation
Robot Intelligence Technology Lab. 15
3. On-line Balance control
}2
1
2
)cos()cos({
})cos()cos(){sin(
)()(
))((})(({})({
)()(
})({})({
)(
})({
2222
2
gglmM
lmM
MM
MM
gzmgzm
xxzzmxzmxxgzzmxgzm
gzmgzm
xzmxzmxgzmxgzmx
M
M
gzm
xzmxgzmx
ub
ua
aA
bB
uiuuii
upupuui
iiiupupuiui
ii
uiuuii
uuuui
iiiuuuiui
ii
ZMPd
A
B
ii
iiiiiiZMPo
On-line compensation equation
Robot Intelligence Technology Lab. 16
3. On-line Balance control
time sampling :
valuepast time sampling one :
valuecurrent :
value predicted :
equation oncompensati momentum axis : )(),,(
equation Difference equation alDifferenti
equation aldifferentiorder 2ndlinear -Non )(),,(
gait line-off by predefined:,
1
1
1111
Ts
Yegf
egf
MMeM
M
MM
MM
exx
n
n
n
nnnn
BAA
B
aA
bB
ZMPoZMPd
Desired ZMP Measured ZMPerror
e = xZMPd - xZMPm
X
Y
o
Continued
Robot Intelligence Technology Lab. 17
3. On-line Balance control
.obtained is angle torso axis-
method Cardano by Solved
equation.order 3rd is equation oncompensati momentum axis-
polynomialorder 3rd:
ly,continuous change onaccelerati and velosity position,error that Assuming
2
1
211
1
11
X
Y
θ
T
T
n
s
nnnn
s
nnn
Continued
Robot Intelligence Technology Lab. 18
4. Experiments
Two phase off-line gait generation
Robot Intelligence Technology Lab. 19
4. Experiments
Online Balance Control
Robot Intelligence Technology Lab. 20
4. Experiments
ZMP trajectory without compensation (pre-designed ZMPx = 15mm)
(a) ZMP trajectory (5 degree tilt)
(b) waist angle trajectory.
Robot Intelligence Technology Lab. 21
4. Experiments
ZMP trajectory with compensation ( at 5 degree tilt)
(b) waist angle trajectory.
(a) ZMP trajectory.
Robot Intelligence Technology Lab. 22
4. Experiments
Ongoing research: HuroSot
Robot Intelligence Technology Lab. 23
5. Conclusions
This paper has presented an overview of research development in humanoid robot HanSaRam.
The off-line gait generation method and the on-line compensation algorithm was proposed. By putting arm-swinging motion in the off-line gait generation
stage, the yawing moment could be cancelled. ZMP compensation has been accomplished by moving the upper
body front and rear in on-line walking.