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-
tim
e
is
ch
allen
g
in
g
d
u
e
to
th
e
h
ig
h
am
o
u
n
t
o
f
co
m
p
u
tatio
n
,
ac
c
u
r
ac
y
r
eq
u
ir
e
m
en
ts
o
f
m
o
d
el
s
,
an
d
f
ast
o
p
tim
izatio
n
s
o
lv
er
[
3
]
.
T
h
is
wo
r
k
ad
d
r
ess
es
th
ese
lim
itatio
n
s
wi
th
p
r
ac
tical,
co
n
s
tr
ain
ed
MPC
alg
o
r
ith
m
s
ca
p
a
b
le
o
f
r
ea
l
-
ti
m
e
ex
ec
u
tio
n
wh
ile
b
ein
g
r
ea
s
o
n
a
b
le
r
o
b
u
s
t,
ac
cu
r
ate,
an
d
s
af
e.
I
n
th
is
wo
r
k
,
we
p
r
o
v
id
ed
a
u
n
if
ied
f
r
a
m
e
wo
r
k
f
o
r
d
esig
n
in
g
co
n
s
tr
ain
ed
MPC
co
n
tr
o
ller
s
f
o
r
th
e
r
o
b
o
tic
m
a
n
ip
u
lato
r
[
4
]
.
T
h
e
p
r
o
p
o
s
ed
p
r
o
ce
s
s
co
n
s
is
ted
o
f
d
er
iv
in
g
an
ac
cu
r
at
e
an
d
v
alid
s
tate
-
s
p
ac
e
m
o
d
el
o
f
th
e
m
an
ip
u
lato
r
,
f
o
r
m
u
latin
g
a
co
n
s
tr
ain
ed
o
p
tim
izatio
n
p
r
o
b
lem
,
an
d
im
p
lem
en
tin
g
a
e
f
f
ici
en
t
r
ea
l
-
tim
e
s
o
lv
er
f
o
r
r
ea
l
-
tim
e
e
x
ec
u
tio
n
.
T
h
e
o
r
etica
l
co
n
s
id
er
atio
n
s
an
d
a
co
m
p
lete
im
p
lem
en
tatio
n
o
f
b
o
th
lin
ea
r
a
n
d
n
o
n
lin
ea
r
MPC
ap
p
r
o
ac
h
es
ar
e
p
r
o
v
id
ed
,
with
n
u
m
e
r
ical
a
n
d
ex
p
er
im
en
tal
v
alid
atio
n
o
n
r
o
b
o
tic
p
latf
o
r
m
s
with
u
p
to
s
ix
d
eg
r
ee
s
o
f
f
r
ee
d
o
m
[
5
]
.
T
h
e
s
u
f
f
icien
t p
er
f
o
r
m
an
ce
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
s
r
ein
f
o
r
ce
s
t
h
e
f
ac
t
th
at
in
co
m
p
licated
tr
ajec
to
r
ies
an
d
f
o
r
d
y
n
am
ically
ch
a
n
g
ed
co
n
s
tr
ain
ts
MPC
o
u
tp
er
f
o
r
m
ed
co
n
v
en
tio
n
al
co
n
tr
o
ller
s
b
y
a
m
ea
s
u
r
ab
le
m
ar
g
in
.
2.
M
E
T
H
O
DO
L
O
G
Y
T
h
e
b
lo
c
k
d
iag
r
am
o
f
d
ev
e
lo
p
m
en
t
o
f
co
n
s
tr
ain
ed
MP
C
Alg
o
r
ith
m
s
f
o
r
Mu
lti
-
DOF
R
o
b
o
tic
Ma
n
ip
u
lato
r
s
illu
s
tr
ated
in
Fig
u
r
e
1
d
em
o
n
s
tr
ates
th
e
s
tep
-
by
-
s
tep
ap
p
r
o
ac
h
to
in
co
r
p
o
r
atin
g
a
MPC
f
r
am
ewo
r
k
to
a
r
o
b
o
tic
s
y
s
tem
with
m
u
ltip
le
d
eg
r
ee
s
o
f
f
r
ee
d
o
m
(
DOF)
[
6
]
.
T
h
is
o
v
er
a
ll
co
n
tr
o
l
s
tr
u
ctu
r
e
allo
ws
r
o
b
o
tics
m
an
ip
u
lato
r
s
to
p
lan
an
d
ex
ec
u
te
m
o
tio
n
b
ased
o
n
th
eir
d
y
n
am
ic
m
o
d
el
an
d
o
p
e
r
atio
n
al
r
eq
u
ir
em
e
n
ts
.
All w
h
ile
p
er
f
o
r
m
in
g
u
n
d
er
a
n
o
p
tim
ized
p
er
f
o
r
m
an
ce
.
Fig
u
r
e
1
.
B
lo
ck
d
iag
r
am
o
f
c
o
n
s
tr
ain
ed
MPC
alg
o
r
ith
m
s
f
o
r
m
u
lti DOF
r
o
b
o
tic
m
an
ip
u
lato
r
s
2
.
1
.
Dy
na
m
ics mo
del
T
h
e
d
y
n
am
ic
m
o
d
el
o
f
th
e
r
o
b
o
tic
m
an
ip
u
lato
r
is
co
n
s
tr
u
cte
d
u
s
in
g
s
o
m
e
o
f
th
e
p
h
y
s
ical
l
aws
wh
ich
d
r
iv
e
th
e
m
o
tio
n
o
f
th
e
m
an
i
p
u
lato
r
,
s
u
ch
as
th
e
New
to
n
-
E
u
ler
o
r
L
ag
r
an
g
ian
f
o
r
m
u
latio
n
s
.
T
h
e
d
y
n
a
m
ic
m
o
d
el
p
r
o
v
i
d
es
in
f
o
r
m
atio
n
a
b
o
u
t
t
h
e
m
a
n
ip
u
lato
r
’
s
m
ass
es,
jo
in
t
to
r
q
u
es,
i
n
er
tias
,
etc.
an
d
a
n
y
o
th
er
n
o
n
-
lin
ea
r
in
ter
ac
tio
n
s
p
r
esen
t
b
et
wee
n
ea
ch
o
f
th
e
lin
k
s
[
7
]
.
I
t
is
im
p
o
r
ta
n
t
to
en
s
u
r
e
th
at
m
o
d
ellin
g
is
d
o
n
e
ac
cu
r
ately
,
s
in
ce
th
e
v
alu
e
o
f
an
y
MPC
is
lin
k
ed
to
h
o
w
clo
s
ely
th
e
m
o
d
el
ca
n
r
ep
licate
t
h
e
b
eh
a
v
io
u
r
o
f
th
e
ac
tu
al
s
y
s
tem
.
2
.
2
.
Co
ns
t
ra
ints
T
h
e
co
n
s
tr
ain
ts
s
p
ec
if
ied
f
o
r
d
esig
n
an
d
im
p
lem
e
n
tatio
n
o
f
MPC
ar
e
v
er
y
im
p
o
r
tan
t
wh
e
n
en
s
u
r
in
g
th
at
th
e
o
p
er
atio
n
s
ar
e
clo
s
e
to
th
e
ac
tu
al
o
p
er
atio
n
s
with
n
o
n
lin
ea
r
co
n
ten
ts
[
8
]
.
T
h
ese
m
ay
co
n
s
is
t
o
f
p
h
y
s
ical
co
n
s
tr
ain
ts
lik
e
jo
i
n
t
lim
its
,
an
d
b
o
u
n
d
s
o
n
v
elo
city
m
o
n
ito
r
in
g
o
r
ac
c
eler
atio
n
,
o
p
er
atio
n
a
l
co
n
s
tr
ain
ts
lik
e
task
s
p
ac
e
lim
its
,
o
r
co
llis
io
n
a
v
o
id
a
n
ce
,
o
r
en
v
ir
o
n
m
en
tal
co
n
s
tr
ain
ts
co
n
s
is
tin
g
o
f
o
b
s
tacle
s
o
r
wo
r
k
s
p
ac
e
lim
its
.
I
n
clu
d
in
g
th
ese
c
o
n
s
tr
ain
ts
en
s
u
r
es
th
at
f
o
r
all
c
o
m
p
u
tatio
n
s
u
s
in
g
t
h
e
m
o
d
el,
th
e
r
o
b
o
t
is
g
u
ar
an
teed
to
b
e
o
p
er
atin
g
s
af
ely
an
d
with
in
ac
ce
p
tab
le
p
e
r
f
o
r
m
a
n
ce
lev
els
[
9
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
C
o
n
s
tr
a
in
ed
C
o
n
s
tr
a
in
ed
mo
d
el
p
r
ed
ictive
co
n
tr
o
l fo
r
en
h
a
n
ce
d
tr
a
jecto
r
y
… (
S
h
y
a
ma
la
g
o
w
r
i Mu
r
u
g
esa
n
)
333
2
.
3
.
Co
ns
t
ra
ined M
P
C
des
ig
n
A
d
y
n
am
ic
m
o
d
el
o
f
th
e
s
y
s
tem
is
u
s
ed
,
an
d
th
e
ad
v
an
ce
d
co
n
tr
o
l
s
tr
ateg
y
,
M
o
d
el
Pre
d
ictiv
e
C
o
n
tr
o
l
s
y
s
tem
,
esti
m
ates
f
u
tu
r
e
s
tates
with
in
a
p
r
ed
eter
m
i
n
ed
p
r
e
d
ictio
n
h
o
r
iz
o
n
.
T
h
e
o
p
t
im
al
co
n
tr
o
l
in
p
u
ts
ar
e
ca
lcu
lated
b
y
s
o
lv
in
g
an
o
p
tim
is
atio
n
p
r
o
b
lem
as
th
e
d
e
f
in
ed
co
n
t
r
o
l
in
ter
v
al
o
cc
u
r
s
[
1
0
]
.
T
h
is
m
eth
o
d
o
f
co
n
tr
o
l
tak
es
th
e
s
y
s
tem
d
y
n
a
m
ics
an
d
co
n
s
tr
ain
ts
in
to
co
n
s
id
er
atio
n
,
m
ea
n
in
g
t
h
e
r
o
b
o
t
ic
m
an
ip
u
lato
r
ca
n
r
esp
ec
t a
ll c
o
n
s
tr
ain
ts
an
d
m
in
im
ize
a
s
p
ec
if
ied
co
s
t f
u
n
ctio
n
wh
ile
tr
ac
k
in
g
a
tar
g
et
tr
ajec
t
o
r
y
o
r
ar
r
i
v
in
g
at
a
s
p
ec
if
ic
co
m
m
an
d
p
o
s
itio
n
.
2
.
4
.
P
re
dict
io
n
m
o
del
T
h
e
MPC
u
s
es
th
e
p
r
ed
ictio
n
m
o
d
el
to
s
im
u
late
th
e
r
o
b
o
t
’
s
f
u
tu
r
e
ac
tiv
ity
b
ased
o
n
p
r
io
r
ac
tiv
it
y
an
d
cu
r
r
e
n
t
s
tate.
T
h
is
al
lo
ws
th
e
MPC
a
lg
o
r
ith
m
to
p
r
ed
ict
h
o
w
th
e
r
o
b
o
t
will
r
esp
o
n
d
to
p
r
ed
ef
in
e
d
co
n
tr
o
l
in
p
u
ts
,
b
ased
o
n
r
o
b
o
t d
y
n
am
i
cs.
T
h
e
m
o
d
el
ca
n
eith
er
b
e
a
l
in
ea
r
is
ed
d
y
n
am
ics m
o
d
el
o
r
n
o
n
lin
ea
r
d
y
n
am
ics
m
o
d
el,
b
ased
o
n
t
h
e
c
o
m
p
lex
i
ty
lev
els
an
d
p
r
o
ce
s
s
in
g
p
o
we
r
v
ast
am
o
u
n
ts
if
an
y
d
ata
in
c
r
ea
s
es
u
n
ce
r
tain
ty
an
d
v
ar
ia
b
ilit
y
wh
en
p
r
ed
ictin
g
an
d
o
p
tim
is
in
g
[
1
1
]
.
2
.
4
.
I
nitia
l st
a
t
e/co
ntr
o
l inpu
t
T
h
e
MPC
o
b
tain
s
th
e
in
itial st
ate
an
d
th
e
in
itial c
o
n
tr
o
l in
p
u
t,
in
o
r
d
er
to
s
tar
t th
e
MPC
o
p
tim
is
atio
n
.
T
h
e
in
itial
s
tate
in
p
u
t
co
n
s
is
t
s
o
f
th
e
cu
r
r
en
t
jo
in
t
p
lace
m
e
n
ts
,
v
elo
cities
an
d
an
y
ad
d
iti
o
n
al
n
ee
d
ed
s
en
s
o
r
f
ee
d
b
ac
k
.
T
h
e
in
itial
s
tate
in
p
u
ts
ar
e
im
p
o
r
tan
t,
s
in
ce
th
e
y
i
n
f
lu
en
ce
t
h
e
q
u
ality
o
f
p
r
e
d
ictio
n
an
d
th
e
q
u
ality
o
f
th
e
o
p
tim
is
atio
n
o
u
tp
u
t,
in
it
ial
s
tate
in
p
u
t m
u
s
t b
e
ac
cu
r
at
e
in
o
r
d
e
r
to
o
b
tain
a
r
elia
b
le
o
u
tp
u
t
[
1
2
]
.
2
.
5
.
M
ulti
-
DO
F
ro
bo
t
ic
m
a
n
ipu
la
t
o
r
Fin
ally
,
th
e
m
u
lti
-
DOF
r
o
b
o
tic
m
an
ip
u
lato
r
is
r
ec
eiv
in
g
th
e
o
u
tp
u
t
o
f
th
e
lim
ited
MPC
[
1
3
]
.
T
h
e
m
an
ip
u
lato
r
is
m
o
v
ed
o
b
s
er
v
e
d
s
tate
an
d
th
e
d
y
n
am
ics
m
o
d
el
b
ased
o
n
th
e
co
n
tr
o
l
c
o
m
m
an
d
s
th
at
ar
e
b
ein
g
ex
ec
u
ted
.
Af
te
r
ac
tu
atio
n
,
th
e
MPC
lo
o
p
will c
o
n
tin
u
e,
a
n
d
th
e
f
ee
d
b
ac
k
is
tak
en
ag
ai
n
to
u
p
d
ate
th
e
s
tate.
2
.
6
.
M
ulti
DO
F
ro
bo
t
ic
m
a
n
ipu
la
t
o
r
s
et
up
Fig
u
r
e
2
p
r
esen
t
an
MPC
ar
ch
itectu
r
e
th
at
em
p
lo
y
s
a
r
ea
l
-
ti
m
e
em
b
ed
d
ed
s
y
s
tem
to
co
n
tr
o
l
a
m
u
lti
-
DOF
r
o
b
o
tic
m
an
ip
u
lato
r
an
d
is
au
g
m
en
ted
b
y
p
o
s
itiv
e
s
tat
e
esti
m
atio
n
alg
o
r
ith
m
s
s
u
ch
as
m
o
v
in
g
h
o
r
izo
n
esti
m
atio
n
(
MH
E
)
o
r
E
x
ten
d
e
d
Kalm
an
Fil
ter
(
E
KF)
.
T
h
es
e
ty
p
e
o
f
ad
v
an
ce
d
s
tr
ateg
ies
allo
ws
th
e
R
o
b
o
tic
s
y
s
tem
s
in
a
d
y
n
am
ic
o
r
u
n
ce
r
tain
co
n
d
itio
n
to
p
er
f
o
r
m
b
ette
r
,
ad
ap
tiv
ely
,
a
n
d
co
n
tr
o
lled
w
ith
co
n
s
tr
ain
ts
d
u
e
to
th
is
s
tr
ateg
y
[
1
4
]
.
2
.
7
.
Ref
er
ence
t
ra
j
ec
t
o
ry
g
e
nera
t
o
r
T
h
e
co
n
tr
o
l
p
r
o
ce
s
s
b
eg
i
n
s
with
th
e
R
ef
er
en
ce
T
r
ajec
to
r
y
Gen
er
ato
r
th
at
p
r
o
v
id
es
th
e
r
o
b
o
tic
m
an
ip
u
lato
r
with
m
o
tio
n
p
r
o
f
i
les.
T
h
ese
tr
ajec
to
r
ies
p
r
o
v
id
e
in
f
o
r
m
atio
n
a
b
o
u
t
th
e
d
esire
d
lo
n
g
-
ter
m
m
o
tio
n
o
f
th
e
en
d
-
ef
f
ec
to
r
o
r
jo
in
ts
o
f
th
e
m
an
ip
u
lato
r
.
T
h
ese
p
r
o
f
i
les
m
ay
b
e
d
ev
el
o
p
ed
m
an
u
ally
o
r
au
to
m
atica
lly
d
ep
en
d
i
n
g
o
n
th
e
ex
p
ec
te
d
o
u
tp
u
t
o
f
th
e
ac
tiv
ity
,
s
u
ch
as
p
ath
-
f
o
llo
win
g
,
p
ick
-
a
n
d
-
p
lace
,
o
r
h
u
m
a
n
-
r
o
b
o
t
in
ter
ac
tio
n
[
1
5
]
.
T
h
is
m
o
d
u
le
d
ev
elo
p
s
a
tim
e
-
d
ep
en
d
en
t ser
ies o
f
r
eq
u
ir
e
d
to
r
q
u
es,
v
elo
cit
ies,
o
r
p
o
s
itio
n
s
.
Fig
u
r
e
2
.
Mu
lti DOF
r
o
b
o
tic
m
an
ip
u
lato
r
s
etu
p
2
.
8
.
M
P
C
co
ntr
o
ller
(
re
a
l
-
t
i
m
e
em
bedd
ed
ha
rdwa
re
)
T
h
e
co
r
e
o
f
th
e
s
y
s
tem
is
th
e
MPC
co
n
tr
o
ller
,
im
p
le
m
en
t
ed
o
n
r
ea
l
-
tim
e
em
b
ed
d
e
d
h
a
r
d
war
e
to
en
s
u
r
e
f
ast
an
d
d
eter
m
in
is
tic
ex
ec
u
tio
n
.
MPC
u
s
es
a
m
o
d
el
o
f
th
e
r
o
b
o
t
to
p
r
ed
ict
its
f
u
tu
r
e
b
eh
av
io
u
r
o
v
er
a
f
in
ite
tim
e
h
o
r
iz
o
n
.
At
ea
c
h
co
n
tr
o
l
s
tep
,
it
s
o
lv
es
an
o
p
ti
m
izatio
n
p
r
o
b
lem
th
at
m
in
im
izes
th
e
d
if
f
er
en
ce
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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2
7
2
2
-
2
5
8
6
I
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I
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t
J
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&
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u
to
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l
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1
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2
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J
u
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20
2
6
:
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3
4
0
334
b
etwe
en
th
e
p
r
e
d
icted
s
tates
an
d
th
e
r
ef
er
e
n
ce
tr
ajec
to
r
y
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s
u
b
ject
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n
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tr
ain
ts
lik
e
jo
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t
lim
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to
r
q
u
e
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o
u
n
d
s
,
an
d
o
b
s
tacle
av
o
id
an
ce
[
1
6
]
.
T
h
e
co
n
tr
o
ller
u
s
es
cu
r
r
en
t
an
d
esti
m
ated
s
tates
o
f
th
e
r
o
b
o
t
(
p
r
o
v
id
e
d
b
y
th
e
s
tate
esti
m
ato
r
)
al
o
n
g
with
th
e
r
ef
er
e
n
ce
in
p
u
ts
to
co
m
p
u
te
o
p
tim
al
co
n
tr
o
l
ac
tio
n
s
.
On
ly
th
e
f
ir
s
t
co
n
tr
o
l
in
p
u
t
in
th
e
o
p
tim
ized
s
eq
u
en
ce
is
ap
p
lied
,
an
d
th
e
p
r
o
ce
s
s
r
ep
ea
ts
at
th
e
n
ex
t
tim
e
s
tep
,
f
o
r
m
in
g
a
clo
s
ed
-
lo
o
p
s
y
s
tem
[
1
7
]
.
2
.
9
.
Ro
bo
t
ma
nip
ula
t
o
r
(
m
u
lt
i
-
DO
F
)
T
h
e
r
o
b
o
t
m
an
ip
u
lato
r
ex
e
c
u
tes
th
e
co
n
tr
o
l
c
o
m
m
an
d
s
is
s
u
ed
b
y
th
e
MPC
.
T
h
is
m
an
ip
u
lato
r
ty
p
ically
h
as
m
u
ltip
le
jo
in
ts
(
DOFs
)
,
allo
win
g
it
to
p
er
f
o
r
m
co
m
p
lex
task
s
in
th
r
ee
-
d
im
en
s
io
n
al
s
p
ac
e
[
1
8
]
.
T
h
e
p
e
r
f
o
r
m
an
ce
o
f
th
e
r
o
b
o
t
d
ep
e
n
d
s
o
n
h
o
w
ac
cu
r
ately
it
f
o
llo
ws
th
e
p
la
n
n
ed
tr
ajec
to
r
y
an
d
h
o
w
well
t
h
e
co
n
tr
o
l sy
s
tem
h
an
d
les d
y
n
a
m
ic
in
ter
ac
tio
n
s
an
d
d
is
tu
r
b
an
ce
s
.
2
.
1
0
.
Sta
t
e
esti
m
a
t
o
r
(
E
K
F
/M
H
E
)
T
h
e
State
E
s
tim
ato
r
p
lay
s
a
cr
u
cial
r
o
le
in
p
r
o
v
id
in
g
ac
c
u
r
ate
r
ea
l
-
tim
e
esti
m
ates
o
f
t
h
e
r
o
b
o
t
’
s
in
ter
n
al
s
tates
(
p
o
s
itio
n
,
v
elo
city
,
an
d
p
o
s
s
ib
ly
u
n
m
ea
s
u
r
ed
v
ar
iab
les).
Sin
ce
n
o
t
all
s
tates
ar
e
d
ir
ec
tly
m
ea
s
u
r
ab
le
d
u
e
to
s
en
s
o
r
l
im
itatio
n
s
o
r
n
o
is
e,
E
x
ten
d
e
d
Kalm
an
Fil
ter
s
(
E
KF)
o
r
Mo
v
in
g
Ho
r
iz
o
n
E
s
tim
atio
n
(
MH
E
)
tech
n
iq
u
es
ar
e
em
p
lo
y
ed
.
E
KF
lin
ea
r
ize
s
th
e
s
y
s
tem
m
o
d
el
ar
o
u
n
d
c
u
r
r
en
t
esti
m
ates
an
d
u
p
d
ates
p
r
ed
ictio
n
s
b
ased
o
n
s
en
s
o
r
d
ata
[
1
9
]
.
MH
E
,
o
n
th
e
o
th
er
h
a
n
d
,
u
s
es
a
s
lid
in
g
win
d
o
w
o
f
p
ast
m
ea
s
u
r
em
en
ts
an
d
s
o
lv
es
an
o
p
tim
izatio
n
p
r
o
b
lem
to
i
n
f
er
th
e
m
o
s
t
lik
ely
s
tate
s
eq
u
en
ce
.
T
h
is
esti
m
ated
s
tate
is
th
en
f
ed
b
ac
k
to
th
e
M
PC
co
n
tr
o
ller
f
o
r
u
s
e
in
th
e
n
e
x
t o
p
tim
izatio
n
c
y
cle
[
2
0
]
.
2
.
1
1
.
Sens
o
rs/o
bs
er
v
er
s
T
h
e
b
o
tto
m
o
f
th
e
d
ia
g
r
am
s
h
o
ws
s
en
s
o
r
s
an
d
o
b
s
er
v
er
s
th
at
co
llect
r
aw
d
ata
f
r
o
m
th
e
r
o
b
o
t.
T
h
ese
in
clu
d
e
en
c
o
d
er
s
(
f
o
r
p
o
s
itio
n
)
,
I
MU
s
(
f
o
r
v
elo
city
)
,
to
r
q
u
e
s
en
s
o
r
s
,
an
d
o
th
e
r
f
ee
d
b
ac
k
d
ev
ices.
Ob
s
er
v
er
s
s
u
p
p
lem
en
t
th
e
s
en
s
o
r
s
b
y
p
r
o
v
id
in
g
esti
m
ates
wh
er
e
d
ir
ec
t
m
ea
s
u
r
em
en
t
is
im
p
r
ac
tical.
T
o
g
eth
er
,
th
is
ar
ch
itectu
r
e
s
u
p
p
o
r
ts
h
ig
h
-
p
r
ec
is
io
n
,
f
ee
d
b
ac
k
-
d
r
iv
en
co
n
tr
o
l
o
f
r
o
b
o
tic
m
an
ip
u
lato
r
s
i
n
r
ea
l
-
tim
e
[
1
6
]
.
I
t
co
m
b
in
es
o
p
tim
al
c
o
n
tr
o
l,
r
e
al
-
tim
e
co
m
p
u
tatio
n
,
an
d
r
o
b
u
s
t
s
tate
esti
m
atio
n
to
e
n
s
u
r
e
ef
f
icien
t,
s
af
e,
a
n
d
in
tellig
en
t r
o
b
o
tic
o
p
er
atio
n
in
co
m
p
lex
task
s
.
2
.
1
2
.
Sim
ula
t
io
n r
esu
lt
s
T
h
e
f
ig
u
r
e
g
iv
en
in
t
h
e
Fig
u
r
e
3
p
r
esen
ts
th
e
tim
e
r
esp
o
n
s
es
o
f
a
two
-
d
eg
r
ee
-
of
-
f
r
ee
d
o
m
r
o
b
o
tic
m
an
ip
u
lato
r
u
n
d
e
r
a
co
n
s
tr
ain
ed
MPC
[
2
1
]
.
T
h
e
u
p
p
er
p
l
o
t
d
ep
icts
jo
in
t a
n
g
les q
1
a
n
d
q
2
th
at
s
m
o
o
th
ly
m
o
v
e
f
r
o
m
n
ea
r
-
ze
r
o
v
alu
es
in
to
t
h
e
n
eg
ativ
e,
th
u
s
p
r
o
v
id
in
g
ev
id
en
ce
o
f
co
n
tr
o
lled
m
an
ip
u
latio
n
o
f
th
e
jo
in
t
an
g
les.
T
h
e
lo
wer
p
lo
t
s
h
o
ws
q
1
an
d
q
2
v
elo
cities.
W
h
ile
q
1
r
em
ain
s
co
n
s
tan
t,
q
2
u
n
d
e
r
g
o
es
a
n
u
m
er
ica
l
s
p
ik
e
n
ea
r
0
.
4
5
s
ec
o
n
d
s
,
p
r
e
s
u
m
ab
ly
ar
is
in
g
f
r
o
m
a
d
is
co
n
tin
u
ity
in
t
h
e
m
o
d
el
o
r
h
av
in
g
a
n
u
m
er
ical
in
s
tab
ilit
y
.
C
o
n
s
eq
u
en
tly
,
th
is
b
eh
av
io
r
s
ig
n
if
ies
th
e
im
p
o
r
ta
n
ce
o
f
r
e
-
t
u
n
in
g
th
e
co
n
tr
o
ller
o
r
en
h
a
n
cin
g
s
tate
esti
m
atio
n
to
d
is
co
u
r
ag
e
s
h
a
r
p
d
er
iv
ativ
e
tr
a
n
s
itio
n
s
in
r
ea
l
-
t
im
e
co
n
tr
o
l
[
2
2
]
.
Fig
u
r
e
3
.
Simu
latio
n
r
esu
lts
o
f
jo
in
t a
n
g
les an
d
jo
in
t v
elo
cities
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
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b
&
A
u
to
m
I
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N:
2722
-
2
5
8
6
C
o
n
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tr
a
in
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C
o
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tr
a
in
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ed
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n
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o
l fo
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en
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a
n
ce
d
tr
a
jecto
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S
h
y
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ma
la
g
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i Mu
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335
T
h
e
g
r
a
p
h
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g
iv
e
n
in
t
h
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Fig
u
r
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4
ar
e
t
h
e
k
in
e
m
atic
tr
ac
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o
f
J
o
in
t
1
f
o
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a
d
u
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o
f
5
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ec
o
n
d
s
.
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h
e
p
atter
n
o
f
jo
in
t
p
o
s
itio
n
o
v
e
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tim
e
in
t
h
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to
p
g
r
ap
h
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th
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in
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atter
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ep
r
ese
n
tativ
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f
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m
o
v
em
e
n
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h
e
s
ec
o
n
d
g
r
ap
h
(
v
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in
u
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t
h
e
p
o
s
itio
n
cu
r
v
e
b
u
t
is
ah
ea
d
o
f
it
b
y
9
0
°
in
p
h
ase
b
ec
au
s
e
o
f
h
ar
m
o
n
ic
m
o
tio
n
.
T
h
e
ac
ce
ler
ativ
e
co
u
p
le,
th
e
d
er
iv
ativ
e
o
f
th
e
v
elo
city
,
p
lo
ts
s
in
u
s
o
id
ally
an
d
is
9
0
°
in
p
h
ase
ah
ea
d
o
f
v
el
o
city
.
T
h
is
lik
ely
r
ep
r
esen
ts
a
s
m
o
o
th
test
tr
ac
k
o
r
s
im
u
lated
p
ath
with
well
-
b
eh
av
ed
d
er
i
v
ativ
es,
h
elp
f
u
l
i
n
m
ain
tain
in
g
lo
w
co
n
t
r
o
l
e
f
f
o
r
t
an
d
r
ed
u
cin
g
m
ec
h
an
ical
s
tr
ess
in
th
e
r
o
b
o
t
m
an
ip
u
lato
r
.
Fig
u
r
e
4
.
Simu
latio
n
r
esu
lts
o
f
jo
in
t 1
p
o
s
itio
n
,
v
elo
city
a
n
d
ac
ce
ler
atio
n
f
o
r
th
e
d
u
r
atio
n
5
s
ec
o
n
d
s
Fig
u
r
e
5
is
a
p
lo
t
o
f
t
h
e
p
er
f
o
r
m
an
ce
o
f
a
n
o
p
tim
izatio
n
s
o
lv
er
o
v
er
1
0
s
ec
o
n
d
s
in
a
MPC
co
n
tex
t
.
T
h
e
d
esire
d
in
p
u
t
is
m
ar
k
e
d
b
y
th
e
r
ed
d
ash
ed
lin
e
,
an
d
th
e
o
p
tim
al
co
n
tr
o
l
o
u
tp
u
t
co
m
p
u
t
ed
b
y
th
e
s
o
lv
er
b
y
th
e
b
lu
e
s
o
lid
lin
e.
T
h
e
clo
s
e
m
atch
in
g
o
f
th
e
d
esire
d
co
n
tr
o
l
tr
ajec
to
r
y
with
m
in
i
m
al
d
e
v
iatio
n
b
y
t
h
e
s
o
lv
er
is
ev
id
en
t
f
r
o
m
th
e
n
ea
r
u
n
ity
o
v
er
lap
o
f
t
h
e
two
cu
r
v
es.
T
h
is
in
d
icate
s
th
at
th
e
r
ea
l
-
tim
e
r
estricte
d
o
p
tim
izatio
n
p
r
o
b
lem
is
b
ein
g
o
p
tim
ally
s
o
lv
ed
b
y
th
e
MP
C
alg
o
r
ith
m
an
d
is
g
en
er
atin
g
co
n
tr
o
l
in
p
u
ts
th
at
clo
s
ely
ap
p
r
o
x
im
ate
th
e
d
esire
d
r
ef
er
e
n
ce
[
2
2
]
.
I
n
r
o
b
o
tic
m
an
ip
u
lato
r
h
ig
h
-
p
r
ec
is
io
n
task
s
,
th
is
is
a
r
eq
u
is
ite
p
er
f
o
r
m
an
ce
.
Fig
u
r
e
5
.
Op
tim
izatio
n
s
o
lv
er
in
ter
f
ac
e
o
u
t
p
u
t o
v
er
tim
e
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
a
s
tate
esti
m
ato
r
in
a
f
ee
d
b
ac
k
l
o
o
p
is
illu
s
tr
ated
in
th
e
p
lo
ts
o
f
Fig
u
r
e
6
.
Po
s
itio
n
tr
ac
k
in
g
is
p
lo
tted
i
n
th
e
to
p
g
r
ap
h
,
an
d
h
i
g
h
e
s
tim
atio
n
ac
cu
r
ac
y
is
r
ep
r
esen
ted
b
y
th
e
clo
s
e
p
r
o
x
im
ity
o
f
th
e
tr
u
e
s
tate
(
b
lu
e)
,
m
ea
s
u
r
em
en
t
d
ata
(
r
ed
x
)
,
an
d
esti
m
ated
s
tate
(
g
r
ee
n
d
ash
ed
)
.
Velo
cit
y
tr
ac
k
in
g
is
p
lo
tted
o
n
th
e
b
o
tto
m
g
r
ap
h
.
T
h
e
esti
m
ato
r
ef
f
ec
tiv
ely
f
ilter
s
o
u
t
d
ata
n
o
is
e
an
d
m
o
n
ito
r
s
th
e
tr
u
e
s
tate
with
m
in
im
al
v
ar
iatio
n
.
Desp
ite
s
en
s
o
r
n
o
is
e,
th
e
esti
m
ato
r
(
m
o
s
t
lik
ely
an
E
KF
o
r
MH
E
)
ac
cu
r
atel
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
2
5
8
6
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l
.
1
5
,
No
.
2
,
J
u
n
e
20
2
6
:
331
-
3
4
0
336
r
ec
o
n
s
tr
u
cts
ac
tu
al
s
y
s
tem
s
tates,
p
r
o
v
id
in
g
th
e
co
n
t
r
o
ll
er
ac
cu
r
ate
f
ee
d
b
ac
k
[
2
3
]
.
T
h
is
is
p
ar
ticu
lar
ly
im
p
o
r
tan
t in
r
o
b
o
tic
ap
p
licatio
n
s
wh
er
e
co
n
tr
o
l p
er
f
o
r
m
a
n
ce
is
b
ased
o
n
ac
cu
r
ate
s
tate
in
f
o
r
m
atio
n
.
Fig
u
r
e
6
.
Simu
latio
n
r
esu
lts
o
f
f
ee
d
b
ac
k
b
lo
ck
p
o
s
itio
n
a
n
d
v
elo
city
J
o
in
t
1
’
s
co
n
tr
o
l
p
er
f
o
r
m
a
n
c
e
u
n
d
er
MPC
with
co
n
s
tr
ain
ts
is
ev
alu
ated
in
th
e
p
lo
t
d
ep
icted
in
Fig
u
r
e
7
.
C
o
n
s
tr
ain
t
s
atis
f
ac
ti
o
n
is
illu
s
tr
ated
in
th
e
to
p
p
lo
t,
in
wh
ich
th
e
ac
tu
al
jo
in
t
an
g
le
(
b
lu
e)
r
em
ai
n
s
with
in
th
e
u
p
p
e
r
an
d
lo
we
r
li
m
its
(
b
lack
d
ash
ed
)
an
d
clo
s
ely
tr
ac
k
s
t
h
e
d
esire
d
tr
ajec
to
r
y
(
r
ed
)
.
C
o
n
tr
o
l
in
p
u
t,
wh
ich
is
also
b
o
u
n
d
ed
with
in
g
iv
en
lim
its
an
d
s
h
o
wn
in
th
e
m
id
d
le
f
ig
u
r
e,
s
h
o
ws
h
o
w
ac
tu
ato
r
f
ea
s
ib
ilit
y
is
h
an
d
led
b
y
th
e
MPC
[
2
4
]
.
Pro
p
er
tr
ac
k
in
g
o
f
th
e
tr
ajec
to
r
y
is
v
alid
ated
b
y
th
e
tr
ac
k
in
g
er
r
o
r
,
wh
ich
d
ec
lin
es
s
h
ar
p
ly
an
d
s
ettles
at
less
th
a
n
0
.
0
5
r
ad
in
th
e
b
o
tto
m
f
ig
u
r
e.
Ov
er
all,
d
u
r
in
g
th
e
1
0
-
s
ec
o
n
d
tim
e
f
r
am
e,
th
e
co
n
tr
o
ller
e
n
s
u
r
es b
o
th
p
er
f
o
r
m
an
ce
an
d
co
n
s
tr
ain
t satis
f
ac
tio
n
.
Fig
u
r
e
7
Simu
latio
n
r
esu
lts
o
f
co
n
tr
o
l p
e
r
f
o
r
m
an
ce
o
f
jo
in
t
1
u
n
d
er
MPC
with
co
n
s
tr
ain
ts
J
o
in
t
1
’
s
tr
ac
k
in
g
p
er
f
o
r
m
a
n
ce
with
co
n
s
tr
ain
t
-
awa
r
e
m
a
n
ag
em
en
t
is
illu
s
tr
ated
in
t
h
e
p
lo
t
in
Fig
u
r
e
8
.
T
h
e
d
esire
d
jo
in
t
an
g
le
is
in
d
icate
d
b
y
th
e
r
ed
d
ash
ed
lin
e,
an
d
th
e
ac
tu
al
jo
in
t
an
g
le
b
y
th
e
b
lu
e
lin
e.
T
h
e
u
p
p
er
a
n
d
l
o
wer
jo
i
n
t
an
g
le
lim
its
(
±
2
r
ad
ian
s
)
ar
e
in
d
icate
d
b
y
th
e
b
lack
d
ash
ed
lin
es.
Du
r
i
n
g
t
h
e
10
-
s
ec
o
n
d
in
ter
v
al,
t
h
e
id
ea
l
tr
ajec
to
r
y
is
clo
s
ely
tr
ac
k
e
d
b
y
th
e
r
ea
l
tr
ajec
to
r
y
with
o
u
t
v
io
latin
g
th
e
co
n
s
tr
ain
ts
[
2
5
]
.
T
h
is
in
d
icat
es
h
o
w
well
th
e
co
n
tr
o
l
alg
o
r
ith
m
,
p
r
esu
m
ab
l
y
MPC
,
im
p
lem
en
ts
p
h
y
s
ical
co
n
s
tr
ain
ts
wh
ile
m
ain
tain
i
n
g
ac
cu
r
ate
tr
ajec
to
r
y
tr
ac
k
in
g
.
I
n
r
o
b
o
tic
m
an
i
p
u
lato
r
task
s
s
u
ch
as
jo
in
t
-
s
p
ac
e
co
n
s
tr
ain
t m
an
ag
e
m
en
t,
th
e
c
o
n
tr
o
ller
en
s
u
r
es a
cc
u
r
ate
an
d
s
af
e
m
o
tio
n
.
T
h
is
p
lo
t
s
h
o
wn
in
Fig
u
r
e
9
r
ep
r
esen
ts
th
e
MPC
tr
ac
k
i
n
g
p
er
f
o
r
m
an
ce
f
o
r
a
m
u
lti
-
d
eg
r
ee
-
of
-
f
r
ee
d
o
m
(
DOF)
r
o
b
o
t,
s
h
o
win
g
th
e
an
g
les
o
f
th
r
ee
in
d
iv
id
u
al
jo
in
ts
o
v
er
tim
e.
E
ac
h
s
u
b
p
lo
t
illu
s
tr
ates
th
e
“
Actu
al
”
jo
in
t
an
g
le
(
b
lu
e
s
o
li
d
lin
e)
tr
ac
k
in
g
t
h
e
“
R
ef
er
en
c
e
”
tr
ajec
to
r
y
(
r
ed
d
ash
ed
lin
e)
.
T
h
e
“
C
o
n
s
tr
ain
ts
”
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
C
o
n
s
tr
a
in
ed
C
o
n
s
tr
a
in
ed
mo
d
el
p
r
ed
ictive
co
n
tr
o
l fo
r
en
h
a
n
ce
d
tr
a
jecto
r
y
… (
S
h
y
a
ma
la
g
o
w
r
i Mu
r
u
g
esa
n
)
337
(
b
lack
d
ash
ed
lin
es)
in
d
icate
th
e
allo
wab
le
o
p
er
atin
g
r
an
g
e
f
o
r
ea
ch
jo
in
t.
T
h
e
p
lo
ts
d
em
o
n
s
tr
ate
th
at
th
e
MPC
ef
f
ec
tiv
ely
co
n
tr
o
ls
th
e
r
o
b
o
t
j
o
in
ts
to
f
o
llo
w
t
h
e
d
esi
r
ed
r
ef
e
r
en
ce
a
n
g
les
wh
ile
r
esp
ec
tin
g
th
e
d
ef
in
e
d
an
g
u
lar
lim
its
,
s
h
o
wca
s
in
g
s
tab
le
an
d
c
o
n
s
tr
ain
ed
m
o
tio
n
[
2
6
]
.
Fig
u
r
e
8
.
Simu
latio
n
r
esu
lts
o
f
tr
ac
k
in
g
p
er
f
o
r
m
an
ce
o
f
J
o
in
t
1
u
n
d
er
co
n
s
tr
ain
ts
T
h
e
g
r
a
p
h
s
h
o
wn
i
n
Fig
u
r
e
1
0
illu
s
tr
ates
th
e
MPC
to
r
q
u
e
i
n
p
u
ts
ap
p
lie
d
to
th
r
ee
r
o
b
o
t
jo
in
ts
o
v
er
a
5
-
s
ec
o
n
d
in
ter
v
al.
E
ac
h
s
u
b
p
lo
t
v
is
u
alize
s
th
e
t
o
r
q
u
e
co
m
m
an
d
(
in
m
ag
e
n
ta)
f
o
r
a
j
o
in
t,
as
well
as
its
co
n
s
tr
ain
ts
(
in
b
lac
k
d
ash
e
d
li
n
es).
T
h
e
c
o
n
tr
o
ller
g
e
n
er
ally
co
m
m
an
d
s
a
h
ig
h
to
r
q
u
e
t
o
co
r
r
ec
t
f
o
r
th
e
i
n
itial
s
tate
er
r
o
r
,
b
ef
o
r
e
s
ettlin
g
q
u
i
ck
ly
in
to
a
s
tab
le
r
eg
im
e
th
at
h
o
ld
s
th
e
in
p
u
ts
b
elo
w
th
e
ass
o
ciate
d
co
n
s
tr
ain
ts
.
T
h
is
is
a
clea
r
d
em
o
n
s
tr
atio
n
o
f
th
e
co
n
tr
o
ller
’
s
a
b
ilit
y
to
r
ap
id
ly
d
r
i
v
e
th
e
s
y
s
tem
to
war
d
s
its
d
esire
d
s
tate
wh
ile
r
esp
ec
tin
g
th
e
p
h
y
s
ical
to
r
q
u
e
co
n
s
tr
ain
ts
.
C
lear
ly
d
em
o
n
s
tr
atin
g
th
is
ty
p
e
o
f
b
eh
a
v
io
r
is
im
p
o
r
tan
t
f
o
r
s
af
e
an
d
ef
f
icien
t
r
o
b
o
tic
m
o
ti
o
n
in
a
p
p
licatio
n
s
wh
er
e
th
e
r
e
ar
e
s
tr
ict
lim
itatio
n
s
o
n
th
e
ac
tu
atio
n
.
Fig
u
r
e
9
.
Simu
latio
n
r
esu
lts
o
f
m
u
lti
DOF
r
o
b
o
t jo
in
t a
n
g
les
MPC
tr
ac
k
in
g
Fig
u
r
e
10
.
Simu
latio
n
r
esu
lts
o
f
MPC
co
n
tr
o
l in
p
u
ts
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
2
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8
6
I
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1
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2
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J
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20
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:
331
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3
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338
3.
CO
NCLU
SI
O
N
T
h
e
p
r
o
p
o
s
ed
wo
r
k
s
u
cc
ess
f
u
lly
d
ev
elo
p
ed
an
d
d
em
o
n
s
tr
ated
a
co
n
s
tr
ain
ed
MPC
alg
o
r
ith
m
f
o
r
m
u
lti
-
d
eg
r
ee
-
of
-
f
r
ee
d
o
m
(
DO
F)
r
o
b
o
tic
m
an
ip
u
lato
r
s
.
T
h
e
MPC
f
r
am
ewo
r
k
c
o
n
s
is
ts
o
f
u
s
in
g
a
p
r
ed
ictio
n
m
o
d
el,
a
co
s
t
f
u
n
ctio
n
an
d
in
p
u
t/s
tate
co
n
s
tr
ain
ts
to
p
r
o
v
id
e
o
p
tim
al
co
n
tr
o
l
in
p
u
ts
s
u
ch
th
at
jo
in
t
tr
ajec
to
r
y
tr
ac
k
in
g
o
cc
u
r
s
.
T
h
e
s
im
u
latio
n
r
esu
lts
d
em
o
n
s
tr
ate
th
at
t
h
e
alg
o
r
ith
m
k
ep
t
th
e
m
an
ip
u
lato
r
s
tates
with
in
s
af
ety
lim
its
,
wh
ile
p
r
o
d
u
cin
g
s
m
o
o
th
an
d
p
r
ec
is
e
m
o
tio
n
co
n
tr
o
l.
T
h
e
p
r
o
p
o
s
ed
MPC
ap
p
r
o
ac
h
is
well
-
s
u
ited
f
o
r
co
m
p
lex
r
o
b
o
tic
ap
p
licati
o
n
s
th
at
r
eq
u
ir
e
r
ea
l
-
tim
e
a
d
a
p
tiv
e
co
n
tr
o
l
s
in
ce
it
ca
n
ad
d
r
ess
m
u
lti
-
v
ar
iab
le
in
ter
ac
tio
n
s
an
d
co
n
s
tr
ain
ts
.
Fu
tu
r
e
wo
r
k
i
n
clu
d
es
g
en
er
a
lizin
g
th
e
f
r
am
ewo
r
k
to
in
c
o
r
p
o
r
ate
n
o
n
lin
ea
r
d
y
n
am
ics,
d
e
v
elo
p
in
g
a
p
r
ed
i
ctio
n
m
o
d
el
th
at
in
clu
d
es
s
tate
esti
m
atio
n
an
d
u
s
in
g
th
e
m
o
d
if
ied
f
r
a
m
ewo
r
k
to
v
alid
ate
an
ex
p
er
im
en
tal
im
p
l
em
en
tatio
n
o
n
p
h
y
s
ical
r
o
b
o
ti
c
p
latf
o
r
m
s
.
T
h
e
d
ir
ec
tio
n
o
f
f
u
tu
r
e
r
esear
c
h
in
MPC
f
o
r
r
o
b
o
tic
m
an
ip
u
lato
r
s
in
clu
d
es
n
o
n
lin
ea
r
MPC
with
an
e
x
ac
t
d
y
n
am
ics
s
y
s
tem
m
o
d
el,
MPC
in
teg
r
ated
with
Kalm
an
Fil
ter
s
to
in
co
r
p
o
r
ate
s
tate
esti
m
atio
n
,
I
m
p
lem
en
tin
g
MPC
in
r
e
al
-
tim
e,
em
b
ed
d
ed
s
y
s
tem
s
,
R
o
b
u
s
t
an
d
s
to
ch
a
s
tic
f
o
r
m
u
latio
n
s
o
f
th
e
c
o
n
tr
o
llab
le
s
y
s
tem
m
o
d
el,
u
s
in
g
m
u
lti
-
o
b
jectiv
e
o
p
tim
izatio
n
f
o
r
task
s
r
elate
d
to
en
er
g
y
e
f
f
icien
cy
o
r
c
o
llis
io
n
av
o
id
a
n
ce
;
an
d
E
n
h
an
ci
n
g
MPC
tech
n
iq
u
es
u
s
in
g
m
ac
h
in
e
lea
r
n
in
g
to
d
e
v
elo
p
ad
ap
tiv
e
,
task
awa
r
e
co
n
tr
o
l.
ACK
NO
WL
E
DG
M
E
N
T
S
T
h
e
au
th
o
r
s
wo
u
ld
lik
e
to
e
x
p
r
ess
th
eir
s
in
ce
r
e
g
r
atitu
d
e
to
all
in
d
iv
id
u
als
an
d
in
s
titu
tio
n
s
wh
o
p
r
o
v
id
e
d
v
alu
ab
le
s
u
p
p
o
r
t
an
d
ass
is
tan
ce
d
u
r
in
g
th
e
co
u
r
s
e
o
f
th
is
r
esear
ch
.
T
h
e
a
u
th
o
r
s
c
o
n
f
ir
m
th
at
c
o
n
s
en
t
h
as b
ee
n
o
b
tain
ed
f
r
o
m
all
in
d
iv
id
u
als ac
k
n
o
wled
g
ed
in
t
h
is
s
ec
tio
n
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
e
au
th
o
r
s
d
ec
lar
e
th
at
n
o
f
u
n
d
in
g
,
g
r
a
n
t,
o
r
o
th
er
f
in
an
cial
s
u
p
p
o
r
t
was
r
ec
eiv
e
d
f
o
r
t
h
e
co
n
d
u
ct
o
f
th
is
r
esear
ch
wo
r
k
.
T
h
e
au
t
h
o
r
s
s
tate
th
at
n
o
f
u
n
d
i
n
g
was in
v
o
lv
ed
in
t
h
is
s
tu
d
y
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
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ed
iT)
to
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ec
o
g
n
ize
in
d
iv
id
u
al
au
th
o
r
co
n
tr
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u
tio
n
s
,
r
ed
u
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au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
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co
llab
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atio
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.
Na
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Aut
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Go
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ath
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h
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ah
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R
am
esh
Po
n
n
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y
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C
:
C
o
n
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p
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f
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ter
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ip
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l
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wo
r
k
r
e
p
o
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ted
in
th
is
p
ap
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.
T
h
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au
th
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s
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lict o
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t
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est.
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h
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o
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tain
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m
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co
n
s
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f
r
o
m
all
in
d
iv
id
u
als
in
clu
d
ed
i
n
th
is
s
tu
d
y
.
All
p
ar
ticip
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ts
p
r
o
v
id
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c
o
n
s
en
t
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r
io
r
t
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th
eir
in
clu
s
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n
i
n
th
e
r
esear
c
h
,
an
d
th
ei
r
p
r
i
v
ac
y
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d
co
n
f
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tiality
h
av
e
b
ee
n
ap
p
r
o
p
r
iately
p
r
o
tecte
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
C
o
n
s
tr
a
in
ed
C
o
n
s
tr
a
in
ed
mo
d
el
p
r
ed
ictive
co
n
tr
o
l fo
r
en
h
a
n
ce
d
tr
a
jecto
r
y
… (
S
h
y
a
ma
la
g
o
w
r
i Mu
r
u
g
esa
n
)
339
E
T
H
I
CAL AP
P
RO
V
AL
T
h
e
r
esear
ch
c
o
n
d
u
cted
in
th
is
s
tu
d
y
co
m
p
lied
with
all
r
elev
an
t
n
atio
n
al
r
e
g
u
latio
n
s
an
d
in
s
titu
tio
n
al
p
o
licies
an
d
was
ca
r
r
ied
o
u
t
in
ac
co
r
d
a
n
ce
with
th
e
eth
ica
l
p
r
in
cip
les
o
f
th
e
Helsin
k
i
Dec
lar
atio
n
.
E
th
ical
ap
p
r
o
v
al
f
o
r
th
e
s
tu
d
y
was o
b
t
ain
ed
f
r
o
m
th
e
I
n
s
titu
tio
n
al
R
ev
iew
B
o
ar
d
/ E
th
ics C
o
m
m
itt
ee
o
f
th
e
r
esp
ec
tiv
e
in
s
titu
tio
n
.
I
n
f
o
r
m
ed
co
n
s
en
t
was
o
b
tain
ed
f
r
o
m
all
in
d
iv
id
u
als
in
clu
d
ed
in
th
is
s
tu
d
y
,
an
d
all
n
ec
ess
ar
y
m
ea
s
u
r
es
wer
e
tak
en
to
en
s
u
r
e
th
e
p
r
iv
ac
y
an
d
c
o
n
f
id
e
n
tiality
o
f
th
e
p
ar
ticip
an
ts
.
T
h
is
s
tu
d
y
d
o
es
n
o
t
i
n
v
o
lv
e
h
u
m
an
p
ar
ticip
an
ts
o
r
a
n
im
als;
th
er
ef
o
r
e,
eth
ical
ap
p
r
o
v
al
a
n
d
in
f
o
r
m
ed
c
o
n
s
en
t w
er
e
n
o
t r
eq
u
ir
ed
.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
au
th
o
r
s
co
n
f
ir
m
th
at
th
e
d
ata
s
u
p
p
o
r
tin
g
th
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
ar
e
av
ailab
le
with
in
th
e
ar
ticle
an
d
its
s
u
p
p
lem
e
n
tar
y
m
ater
ials
.
Ad
d
itio
n
al
d
ata
r
elate
d
to
th
is
s
tu
d
y
ar
e
av
ailab
le
f
r
o
m
th
e
co
r
r
esp
o
n
d
in
g
au
th
o
r
u
p
o
n
r
ea
s
o
n
a
b
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
J.
S
o
n
,
H
.
K
a
n
g
,
a
n
d
S
.
H
.
K
a
n
g
,
“
A
r
e
v
i
e
w
o
n
r
o
b
u
s
t
c
o
n
t
r
o
l
o
f
r
o
b
o
t
man
i
p
u
l
a
t
o
r
s
f
o
r
f
u
t
u
r
e
ma
n
u
f
a
c
t
u
r
i
n
g
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
Pre
c
i
si
o
n
E
n
g
i
n
e
e
ri
n
g
a
n
d
Ma
n
u
f
a
c
t
u
r
i
n
g
,
v
o
l
.
2
4
,
n
o
.
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c
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.
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