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eq
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[
1
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2]
.
T
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tan
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f
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latin
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[
3
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t b
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if
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ativ
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Ho
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till
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I
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Ta
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301
b
ef
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r
e
im
p
lem
en
tatio
n
in
a
r
e
al
en
v
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n
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ca
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b
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a
ch
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m
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test
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d
th
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p
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b
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s
d
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cu
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in
Sectio
n
1.
In
Sectio
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2,
a
b
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liter
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e
r
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v
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T
h
e
in
itial
r
esu
lt
s
wer
e
an
aly
ze
d
in
Sectio
n
4.
T
h
e
p
ap
er
is
co
n
clu
d
ed
in
Sectio
n
5.
2.
RE
L
AT
E
D
WO
RK
S
T
h
e
r
esear
c
h
wo
r
k
s
on
a
co
ll
ab
o
r
atio
n
of
HR
I
th
at
is
in
cr
e
asin
g
g
r
a
d
u
ally
in
t
h
is
ad
v
a
n
ce
d
wo
r
l
d
.
Ad
d
in
g
th
e
s
af
ety
f
ac
to
r
an
d
t
h
e
d
an
g
er
lev
el
d
u
r
i
n
g
HR
I
h
av
e
b
ec
o
m
e
th
e
ce
n
tr
e
of
th
e
attr
ac
tio
n
am
o
n
g
all
r
esear
ch
er
s
.
Still
,
th
er
e
is
v
er
y
little
f
o
cu
s
on
HR
I
in
th
e
in
d
o
o
r
e
n
v
ir
o
n
m
en
t.
In
f
ac
t,
th
e
s
y
s
tem
ic
an
aly
s
es
of
HR
I
in
th
e
d
o
m
esti
c
en
v
ir
o
n
m
en
t
ar
e
n
o
t
y
et
co
n
d
u
cte
d
.
In
r
ea
lity
,
th
er
e
is
a
lack
of
a
war
en
ess
of
th
e
r
ea
l
th
r
ea
ts
an
d
th
e
s
ec
u
r
ity
p
r
io
r
iti
es
in
v
o
lv
ed
d
u
r
in
g
HR
I
.
L
iter
atu
r
e
o
v
er
v
iews
on
th
is
cr
itical
is
s
u
e
ar
e
d
escr
ib
ed
b
r
ie
f
ly
b
elo
w.
L
er
a
et
a
l.
[
7
]
d
ev
elo
p
e
d
a
tax
o
n
o
m
y
class
if
y
in
g
cy
b
er
-
s
ec
u
r
ity
th
r
ea
ts
tar
g
eted
at
t
h
e
p
r
o
t
ec
tio
n
an
d
s
ec
u
r
ity
of
s
er
v
ice
r
o
b
o
ts
.
T
h
e
p
r
o
p
o
s
ed
tax
o
n
o
m
y
d
if
f
er
e
n
tiates
th
e
r
is
k
s
ac
co
r
d
in
g
to
th
e
ty
p
e
of
u
s
er
f
o
r
s
af
ety
th
r
ea
ts
.
T
h
e
esti
m
ated
r
is
k
s
f
o
r
each
u
s
er
f
o
r
m
s
h
all
be
d
ef
in
e
d
by
th
e
p
h
y
s
ical
i
m
p
ac
t
lev
el
an
d
th
e
s
o
u
r
ce
of
th
e
r
is
k
.
On
ly
u
n
d
er
th
e
r
o
b
o
t
f
ea
tu
r
e
a
n
d
f
o
r
m
of
s
en
s
o
r
f
itted
with
th
e
r
o
b
o
t,
s
ec
u
r
ity
th
r
ea
ts
ar
e
ca
teg
o
r
ized
.
B
o
n
ac
i
et
a
l.
[
8
]
ad
d
r
ess
ed
s
ec
u
r
ity
r
is
k
s
f
o
r
th
e
R
av
en
I
I
,
an
ad
v
an
c
ed
s
u
r
g
ical
d
ev
ice,
teleo
p
er
ated
s
u
r
g
ical
r
o
b
o
t.
T
h
e
au
th
o
r
s
d
em
o
n
s
tr
ated
th
at
in
tr
u
d
er
s
c
o
u
ld
co
n
tr
o
l
a
wid
e
r
an
g
e
of
r
o
b
o
t
f
u
n
ctio
n
s
m
alicio
u
s
ly
by
p
er
f
o
r
m
in
g
i
n
ter
r
u
p
tio
n
s
an
d
m
an
ip
u
latio
n
attac
k
s
a
g
ain
s
t
th
e
wir
eless
co
m
m
u
n
icatio
n
co
n
n
ec
tio
n
b
etwe
en
th
e
s
u
r
g
eo
n
an
d
th
e
r
o
b
o
t.
T
h
e
attac
k
s
a
r
e
b
ased
on
th
e
m
id
d
le
m
an
m
o
d
el
an
d
h
av
e
e
f
f
ec
tiv
ely
af
f
ec
ted
th
e
p
r
o
tectio
n
a
n
d
u
s
ab
ilit
y
of
th
e
o
p
er
atin
g
r
o
b
o
t,
w
h
ich
m
ay
r
esu
lt
in
leg
al
b
r
ea
c
h
es
an
d
p
r
iv
ac
y
.
O
lawo
y
in
[
9
]
r
esear
ch
ed
s
af
ety
an
d
a
u
to
m
atio
n
in
a
c
o
llab
o
r
a
tiv
e
r
o
b
o
t
n
etwo
r
k
in
th
e
wo
r
k
in
g
en
v
ir
o
n
m
e
n
t
a
n
d
co
n
clu
d
e
d
th
at
p
er
f
o
r
m
an
c
e
n
ee
d
s
to
be
im
p
r
o
v
e
d
to
av
o
id
s
af
ety
co
n
s
tr
ain
ts
in
au
to
m
atio
n
an
d
r
o
b
o
tics
-
r
e
lated
is
s
u
es.
Do
m
b
r
o
wsk
i
et
a
l.
[
1
0
]
em
p
h
asized
s
p
ec
if
ic
s
ig
n
if
ican
ce
in
th
e
au
to
m
ated
f
ac
t
o
r
y
s
y
s
tem
s
to
p
r
ep
ar
e
h
u
m
a
n
-
r
o
b
o
t
co
o
p
er
at
io
n
(
HR
C
)
.
W
eits
ch
at
an
d
As
ch
em
an
n
[
1
1
]
h
av
e
d
ev
elo
p
e
d
a
n
ew
a
p
p
r
o
ac
h
t
h
at
s
till
m
ee
ts
th
e
in
ter
n
atio
n
al
s
af
ety
s
tan
d
ar
d
s
of
co
llab
o
r
ativ
e
r
o
b
o
tics
f
o
r
r
o
b
o
t
p
er
f
o
r
m
an
ce
en
h
an
ce
m
en
ts
.
T
h
e
attac
k
s
a
r
e
b
ased
on
a
m
an
-
in
-
th
e
-
m
i
d
d
le
p
ar
a
d
ig
m
.
T
h
ey
h
av
e
ef
f
ec
tiv
ely
im
p
ac
ted
th
e
s
u
r
g
i
ca
l
r
o
b
o
t'
s
p
r
o
tectio
n
an
d
u
s
ab
ilit
y
,
wh
ich
co
u
ld
p
o
ten
tially
lead
to
v
io
latio
n
s
of
law
an
d
p
r
iv
ac
y
.
L
o
u
k
as
et
a
l.
[
1
2
]
ar
g
u
ed
th
at
th
e
r
estricte
d
r
u
le
-
b
ased
or
lig
h
tweig
h
t
m
ac
h
in
e
lear
n
in
g
tech
n
iq
u
es
u
s
ed
in
cy
b
er
-
p
h
y
s
ical
v
eh
icle
in
tr
u
s
io
n
d
etec
tio
n
co
u
ld
be
r
ep
lace
d
by
more
s
o
p
h
is
ticated
me
th
o
d
s
u
s
in
g
clo
u
d
co
m
p
u
ta
tio
n
al
o
f
f
lo
ad
in
g
.
T
h
e
im
p
r
o
v
ed
co
m
p
u
tin
g
p
o
wer
is
u
s
ed
to
in
tr
o
d
u
ce
an
in
-
d
ep
th
m
u
ltil
ay
er
p
er
ce
p
tio
n
a
n
d
r
ec
u
r
r
en
t
n
eu
r
al
n
etwo
r
k
a
r
ch
itectu
r
e
th
at
r
ec
ei
v
es
th
e
c
y
b
er
-
p
h
y
s
ical
d
ata
co
llected
in
th
e
r
o
b
o
tic
v
e
h
icle
in
r
ea
l
-
tim
e
a
n
d
an
aly
ze
s
it
f
o
r
i
n
tr
u
s
io
n
d
etec
tio
n
.
B
atso
n
et
a
l.
[
1
3
]
ca
r
r
ied
out
a
s
tu
d
y
to
id
en
tify
r
i
s
k
s
an
d
wea
k
n
ess
es
in
th
e
u
n
m
an
n
e
d
tactica
l
au
to
n
o
m
o
u
s
co
n
tr
o
l
an
d
co
m
m
u
n
icatio
n
f
r
a
m
ewo
r
k
f
o
r
th
e
s
y
s
tem
.
J
o
n
es
an
d
S
tr
au
b
[
1
4
]
im
p
lem
en
ted
a
t
wo
-
s
tag
e
in
tr
u
s
io
n
d
etec
tio
n
s
y
s
tem
in
au
to
n
o
m
o
u
s
r
o
b
o
ts
f
o
r
d
etec
tin
g
n
etwo
r
k
in
tr
u
s
io
n
s
an
d
m
alwa
r
e.
T
h
e
au
th
o
r
s
u
s
ed
a
d
ee
p
n
eu
r
al
n
etwo
r
k
a
n
d
tau
g
h
t
it
to
d
etec
t
co
m
m
an
d
s
th
at
d
ev
iate
f
r
o
m
p
lan
n
e
d
b
eh
a
v
io
r
.
Vu
o
n
g
et
a
l.
[
1
5
]
h
av
e
s
u
g
g
ested
two
s
ep
ar
ate
m
eth
o
d
s
f
o
r
id
e
n
tify
in
g
r
o
b
o
tic
v
eh
icle
attac
k
s
.
T
h
e
f
ir
s
t
ap
p
r
o
ac
h
was
b
ased
on
th
e
u
s
e
of
d
ec
is
io
n
tr
ee
s
,
an
d
th
e
s
ec
o
n
d
was
b
ased
on
th
e
u
s
e
of
p
r
o
f
o
u
n
d
lear
n
i
n
g
.
Dem
ir
an
d
Du
r
d
u
[
1
6
]
d
em
o
n
s
tr
ated
h
o
w
h
u
m
a
n
an
d
r
o
b
o
t
in
ter
ac
tio
n
c
o
u
ld
be
m
o
n
ito
r
in
an
in
d
o
o
r
p
lace
.
T
h
e
o
b
jectiv
e
of
th
eir
p
r
o
p
o
s
al
was
th
e
h
u
m
an
-
r
o
b
o
t
r
elatio
n
s
h
ip
s
d
e
f
in
e
th
e
m
o
d
els
of
p
eo
p
le'
s
r
o
b
o
t
in
ter
ac
t
io
n
ex
p
ec
tatio
n
s
to
d
ir
ec
t
r
o
b
o
t
d
esig
n
an
d
alg
o
r
i
th
m
ic
cr
ea
tio
n
,
wh
ich
will
m
ak
e
th
e
in
ter
ac
tio
n
b
etwe
en
p
eo
p
le
an
d
r
o
b
o
tics
more
n
atu
r
al
an
d
ef
f
ec
tiv
e.
Ku
m
ar
et
a
l.
[
1
7
]
p
r
o
p
o
s
ed
t
h
e
o
p
tim
u
m
m
o
v
em
e
n
t
co
n
tr
o
l
an
d
tr
ajec
to
r
y
p
la
n
n
in
g
ap
p
r
o
ac
h
to
v
ar
io
u
s
r
o
b
o
t
f
r
ee
d
o
m
s
with
s
o
f
t
ap
p
licatio
n
s
co
m
p
u
tin
g
tec
h
n
iq
u
es
an
d
c
o
m
p
a
r
ativ
e
an
al
y
s
is
also
ev
alu
ated
an
d
s
h
o
w
ed
d
if
f
er
en
t
d
e
g
r
ee
s
of
r
o
b
o
tic
ar
m
f
r
ee
d
o
m
to
co
m
p
en
s
ate
f
o
r
s
u
ch
u
n
ce
r
t
ain
ties
r
o
b
o
tic
ar
m
m
o
v
em
en
t
an
d
ten
s
io
n
b
ef
o
r
e
tim
e
s
ettlin
g
,
o
p
tim
izatio
n
,
th
e
ar
m
m
o
tio
n
of
t
h
e
r
o
b
o
t
,
i.e
.
its
k
i
n
em
atics
b
eh
av
io
r
.
Sh
en
awy
et
a
l.
[
1
8
]
ex
p
lo
r
ed
m
u
lti
r
o
b
o
tics
team
wo
r
k
d
u
r
i
n
g
th
e
ex
p
l
o
r
atio
n
p
h
ase
an
d
co
m
p
ar
e
d
an
d
ev
alu
ated
th
e
s
u
cc
ess
of
v
ar
io
u
s
m
u
lti
-
r
o
b
o
t
ex
p
l
o
r
ati
o
n
p
o
licies
f
o
r
d
if
f
er
en
t
en
v
ir
o
n
m
en
ts
an
d
team
s
izes.
In
co
m
b
in
ato
r
ial
m
eth
o
d
,
th
e
au
th
o
r
[
1
9
]
a
n
aly
ze
d
s
ev
er
al
tech
n
iq
u
es
of
r
e
p
r
esen
tat
io
n
of
th
e
s
p
ac
e
Evaluation Warning : The document was created with Spire.PDF for Python.
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4
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310
302
u
s
in
g
p
r
e
v
io
u
s
r
esear
c
h
an
d
it
s
f
in
d
in
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s
with
v
ar
io
u
s
p
ar
am
eter
s
,
s
u
ch
as
o
p
tim
ality
,
co
m
p
leten
ess
,
s
tab
ilit
y
,
m
em
o
r
y
u
tili
za
tio
n
,
ef
f
ec
tiv
e
tim
e
an
d
co
m
p
u
ter
tim
e
etc.
T
h
e
p
r
o
g
r
am
m
in
g
by
d
em
o
n
s
tr
atio
n
s
y
s
tem
was
p
r
esen
ted
by
Am
ar
et
a
l.
[
2
0
]
on
a
tr
ajec
to
r
y
lev
el
to
r
ep
r
o
d
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ce
h
a
n
d
/to
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e
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with
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o
t
m
an
ip
u
lato
r
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wh
ich
was
ac
h
ie
v
ed
with
th
e
Ar
T
o
o
lk
it,
tr
ac
k
in
g
u
s
er
m
o
v
em
en
t
a
n
d
th
e
tr
ajec
to
r
ies
with
th
e
lim
ited
cu
b
ic
s
p
in
e
r
ewo
r
k
ed
.
Attam
im
i
et
a
l.
[
2
1
]
p
r
o
v
id
e
d
in
a
f
r
ee
p
lay
s
ce
n
ar
io
a
w
ay
to
esti
m
ate
th
e
co
n
ce
n
tr
atio
n
of
an
i
n
f
an
t,
o
n
e
of
th
e
m
o
s
t
cr
itical
m
e
n
tal
s
tates.
I
n
ter
ac
tio
n
b
etwe
en
ch
il
d
an
d
r
o
b
o
t
(
C
R
I
)
.
First,
th
ey
d
ev
elo
p
ed
a
s
y
s
tem
to
f
ee
l
th
e
v
er
b
al
an
d
no
-
v
er
b
al
m
u
ltimo
d
al
s
ig
n
al
of
a
c
h
ild
,
in
clu
d
in
g
g
az
e,
f
ac
ial
ex
p
r
ess
io
n
an
d
p
r
o
x
im
ity
,
to
m
ak
e
a
ca
r
ef
u
l
esti
m
ate
in
th
is
CRI
s
ce
n
ar
io
.
In
o
r
d
er
to
d
eter
m
in
e
an
in
d
iv
id
u
al
atten
tio
n
lev
el,
th
e
o
b
s
er
v
ed
in
f
o
r
m
atio
n
was
th
en
u
s
ed
to
tr
ain
a
m
o
d
el
b
ased
on
a
v
ec
to
r
s
u
p
p
o
r
t
m
ec
h
an
is
m
(
SVM)
.
So
m
e
d
r
a
wb
ac
k
s
of
th
e
p
r
ev
io
u
s
r
esear
ch
er
can
be
d
is
cu
s
s
ed
b
r
ief
ly
b
elo
w
.
‑
I
n
d
u
s
tr
ial
r
o
b
o
tic
s
y
s
tem
s
:
r
o
b
o
ts
ar
e
m
o
s
tly
ca
g
ed
an
d
is
o
lated
f
r
o
m
h
u
m
a
n
s
in
a
s
af
ety
g
u
ar
d
en
v
ir
o
n
m
en
t.
‑
Un
s
tr
u
ctu
r
ed
en
v
ir
o
n
m
e
n
ts
(
d
o
m
esti
c
ar
ea
)
:
Me
ch
an
ical
d
esig
n
alo
n
e
is
not
ad
eq
u
ate
to
en
s
u
r
e
s
af
e
an
d
h
u
m
an
-
f
r
ien
d
l
y
in
ter
ac
tio
n
.
‑
Saf
ety
m
ea
s
u
r
es,
u
tili
zin
g
s
y
s
tem
co
n
tr
o
l
a
n
d
p
lan
n
in
g
,
ar
e
n
ec
ess
ar
y
.
‑
Saf
e
in
ter
ac
tio
n
:
a
r
o
b
o
t
m
u
s
t
ass
es
s
th
e
lev
el
of
d
an
g
er
in
its
cu
r
r
en
t
en
v
ir
o
n
m
en
t,
a
n
d
a
ct
to
m
in
im
ize
th
at
d
an
g
er
.
T
h
u
s
,
th
is
h
as
m
o
tiv
ated
th
i
s
r
esear
ch
s
tu
d
y
to
p
r
o
p
o
s
e
a
s
af
ety
h
u
m
an
-
c
o
b
o
t
co
llab
o
r
atio
n
m
eth
o
d
by
im
p
lem
en
tin
g
th
e
alg
o
r
ith
m
u
s
in
g
a
Gaz
eb
o
s
im
u
lato
r
in
R
OS.
3.
RE
S
E
ARCH
M
E
T
H
O
D
A
m
eth
o
d
o
lo
g
y
f
o
r
s
o
f
twar
e
d
ev
elo
p
m
en
t
is
a
f
r
a
m
ewo
r
k
u
s
ed
to
o
r
g
a
n
ize,
s
ch
ed
u
le,
an
d
m
o
n
ito
r
a
s
y
s
tem
'
s
s
o
f
twar
e
d
ev
elo
p
m
en
t
p
r
o
ce
s
s
.
T
h
is
in
v
o
lv
es
p
r
e
d
ef
in
in
g
u
n
iq
u
e
d
eliv
er
ab
les
an
d
o
b
jects
th
at
a
p
r
o
ject
team
is
d
ev
elo
p
in
g
an
d
co
m
p
letin
g
to
cr
e
ate
or
m
an
ag
e
an
ap
p
licatio
n
[
2
2
]
.
W
h
ile
s
u
cc
ess
f
u
l
tech
n
iq
u
es
f
o
r
th
e
p
r
o
d
u
ctio
n
of
s
af
ety
-
cr
itical
s
o
f
twar
e
ar
e
well
es
tab
lis
h
ed
in
th
e
av
i
o
n
ics
in
d
u
s
tr
y
,
f
o
r
ex
am
p
le,
t
h
ese
tech
n
iq
u
es
ar
e
ty
p
ically
d
esig
n
ed
f
o
r
p
r
o
j
ec
ts
with
a
lo
n
g
tim
e
s
ca
le
an
d
h
i
g
h
le
v
el
of
p
er
s
o
n
n
el.
T
h
is
m
a
y
be
u
n
s
u
itab
le
f
o
r
u
s
e
in
th
e
f
ield
of
g
r
o
u
n
d
b
r
ea
k
in
g
r
o
b
o
tic
s
r
esear
ch
with
o
u
t
ad
ap
tatio
n
,
wh
er
e
tim
escale
is
s
h
o
r
ter
an
d
h
u
m
an
r
eso
u
r
ce
s
an
d
f
in
an
cial
ex
p
en
d
itu
r
e
u
s
u
ally
m
u
ch
lo
wer
[
2
3
]
.
T
y
p
ically
,
one
h
as
to
d
e
al
with
a
wid
e
r
a
n
g
e
of
s
en
s
o
r
s
an
d
ac
tu
ato
r
s
with
v
a
r
y
in
g
ab
ilit
y
lev
els
in
th
e
r
o
b
o
tics
d
o
m
ain
.
Ad
d
in
g
to
t
h
is
d
if
f
icu
lty
of
m
ak
in
g
h
eter
o
g
en
eo
u
s
h
ar
d
war
e
s
y
s
tem
s
,
r
o
b
o
ts
h
av
e
lim
ited
r
eso
u
r
ce
s
to
d
ea
l
with
o
p
en
-
en
d
ed
en
v
ir
o
n
m
en
ts
[
2
4
]
.
In
o
th
er
ar
ea
s
,
th
er
e
is
a
g
r
o
win
g
n
ee
d
to
tailo
r
v
alid
ated
s
o
f
twar
e
en
g
in
ee
r
in
g
ap
p
r
o
ac
h
es
to
th
e
r
o
b
o
tics
r
eq
u
ir
em
en
ts
.
In
t
h
is
d
ir
ec
tio
n
,
a
m
eth
o
d
o
lo
g
y
is
r
eq
u
ir
ed
th
at
d
o
es
n
o
t
co
n
s
tr
ai
n
an
y
p
ar
ticu
lar
ar
c
h
itectu
r
e.
3
.
1
.
Sy
s
t
em
o
v
er
v
iew
Fig
u
r
e
1
s
h
o
ws
th
e
s
y
s
tem
o
v
er
v
iew
o
f
h
u
m
a
n
-
r
o
b
o
t
in
ter
ac
tio
n
.
T
h
e
u
s
er
is
s
u
es
a
co
m
m
an
d
to
s
tar
t
th
e
co
n
tact
with
th
e
r
o
b
o
t.
T
h
e
co
m
m
a
n
d
tr
an
s
lato
r
c
o
n
v
e
r
ts
th
e
in
s
tr
u
ctio
n
in
th
e
n
atu
r
al
lan
g
u
ag
e
in
to
a
s
er
ies
o
f
tar
g
et
p
o
s
itio
n
s
an
d
ac
ts
(
XYZ
p
lan
e)
.
T
h
is
h
u
m
a
n
-
r
o
b
o
t
in
ter
ac
tio
n
m
o
d
el
ca
n
b
e
d
iv
id
ed
i
n
to
a
g
lo
b
al
co
n
tr
o
ller
an
d
a
lo
ca
l
co
n
tr
o
ller
.
T
h
e
g
lo
b
al
co
n
tr
o
l
ler
s
eg
m
en
t
b
eg
in
s
d
esig
n
in
g
a
g
eo
m
etr
ic
co
u
r
s
e
f
o
r
th
e
r
o
b
o
t
o
v
er
lar
g
e
task
s
eg
m
en
ts
.
Seg
m
en
t
en
d
p
o
in
ts
a
r
e
s
p
ec
if
ied
b
y
th
e
lo
ca
tio
n
s
wh
er
e
th
e
r
o
b
o
t
will
s
to
p
an
d
p
er
f
o
r
m
a
m
an
eu
v
er
f
o
r
g
r
ip
o
r
r
elea
s
e.
Fo
r
ex
am
p
le,
it
d
ef
in
e
s
o
n
e
p
at
h
s
eg
m
e
n
t
f
r
o
m
th
e
r
o
b
o
t'
s
in
itial
lo
ca
tio
n
to
th
e
o
b
ject
t
o
b
e
p
ick
ed
u
p
.
T
h
e
l
o
ca
l
p
l
an
n
er
g
en
er
ates
th
e
tr
ajec
to
r
y
alo
n
g
t
h
e
g
lo
b
ally
p
lan
n
ed
p
ath
b
ased
o
n
in
f
o
r
m
atio
n
o
b
tain
ed
i
n
r
ea
l
-
tim
e
d
u
r
in
g
th
e
ex
ec
u
tio
n
o
f
th
e
m
is
s
i
o
n
.
At
ev
er
y
c
o
n
tr
o
l
p
o
in
t,
th
e
lo
ca
l
p
la
n
n
er
p
r
o
d
u
ce
s
th
e
co
n
tr
o
l
s
ig
n
al
r
e
q
u
ir
e
d
.
Sin
ce
th
e
l
o
ca
l
p
lan
n
er
m
a
k
es
u
s
e
o
f
r
ea
l
-
tim
e
in
f
o
r
m
atio
n
,
th
e
tr
ajec
to
r
y
is
p
r
o
d
u
ce
d
in
s
h
o
r
t
s
eg
m
en
ts
.
T
h
e
u
s
er
is
tr
ac
k
ed
d
u
r
in
g
th
e
in
ter
ac
tio
n
to
d
eter
m
in
e
th
e
u
s
er
'
s
ap
p
r
o
v
al
l
ev
el
f
o
r
c
o
b
o
t
b
eh
av
i
o
r
.
T
h
e
lo
ca
l
c
o
n
tr
o
ller
s
eg
m
en
t
u
s
es
th
is
in
f
o
r
m
atio
n
to
m
o
d
if
y
th
e
r
o
b
o
t'
s
v
elo
city
alo
n
g
th
e
ex
p
ec
ted
p
ath
.
At
-
co
n
tr
o
l
p
h
ase,
th
e
s
a
f
ety
co
n
tr
o
l
m
o
d
u
le
ass
ess
es
th
e
s
af
ety
of
t
h
e
p
la
n
cr
ea
te
d
by
th
e
t
r
ajec
to
r
y
p
lan
n
er
.
If
an
e
n
v
ir
o
n
m
en
tal
ch
an
g
e
is
i
d
en
tifie
d
,
wh
ich
t
h
r
ea
ten
s
th
e
s
af
ety
of
th
e
in
te
r
ac
tio
n
,
a
d
ev
iatio
n
f
r
o
m
th
e
p
lan
n
e
d
p
ath
is
tr
ig
g
er
ed
by
t
h
e
s
ec
u
r
ity
co
n
tr
o
l
m
o
d
u
le.
T
h
e
d
ev
iatio
n
wo
u
ld
p
u
s
h
th
e
co
b
o
t
to
a
more
s
ec
u
r
e
s
p
o
t.
C
o
n
cu
r
r
en
tly
,
a
re
-
ev
alu
atio
n
of
th
e
p
r
o
g
r
am
will
be
co
n
d
u
cted
by
th
e
r
eh
ab
ilit
atio
n
ev
alu
ato
r
an
d
re
-
p
lan
n
in
g
,
if
n
ec
ess
ar
y
.
3
.
2
.
Sa
f
et
y
s
t
a
t
e
dia
g
ra
m
Fig
u
r
e
2
illu
s
tr
ates
th
e
s
tep
s
or
p
r
o
ce
s
s
of
s
af
ety
d
u
r
in
g
HR
I
.
In
o
r
d
er
to
lo
ca
te
th
e
s
af
est
co
n
f
ig
u
r
atio
n
,
t
h
e
ar
m
r
o
b
o
t
n
ee
d
s
to
m
o
n
ito
r
a
n
d
go
th
r
o
u
g
h
all
th
e
p
r
o
ce
s
s
es
an
d
,
in
th
e
en
d
,
re
-
p
la
n
h
is
n
ex
t
s
tep
.
If
th
e
ar
m
r
o
b
o
t
n
o
t
in
ac
tio
n
its
ch
ec
k
s
th
e
d
a
n
g
er
lev
el.
If
th
e
d
an
g
er
lev
e
l
is
g
r
ea
ter
th
an
th
e
th
r
esh
o
ld
,
th
e
n
it
is
ac
tiv
atin
g
its
ac
tio
n
.
Af
ter
th
e
co
b
o
t
f
ig
u
r
es
out
th
e
d
a
n
g
er
le
v
el,
it
r
ed
u
ce
s
h
is
s
p
ee
d
an
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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o
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&
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to
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4
8
5
6
A
s
imu
la
ted
r
is
k
a
s
s
es
s
men
t
of
h
u
ma
n
-
r
o
b
o
t
in
tera
ctio
n
in
th
e
d
o
mestic
en
viro
n
men
t
(
Ta
m
a
n
n
a
E
K
a
o
n
a
i
n
)
303
s
lo
ws
d
o
wn
,
an
d
if
th
er
e
is
no
v
el
o
cit
y
,
th
e
n
th
e
co
b
o
t
re
-
p
lan
a
n
d
wait
up
to
r
ec
eiv
e
a
n
ew
p
lan
.
T
h
e
alg
o
r
ith
m
of
th
e
m
et
h
o
d
of
th
i
s
r
esear
ch
is
as
f
o
llo
ws
an
d
illu
s
tr
ated
in
Fig
u
r
e
3
.
‑
Step
1:
I
n
itializatio
n
I
n
itially
,
th
e
ar
m
r
o
b
o
t
s
ea
r
ch
f
o
r
an
y
o
b
s
tacle
s
,
if
it
ca
n
n
o
t
f
in
d
an
y
o
b
s
tacle
s
it
h
as
gone
f
o
r
war
d
.
‑
Step
2:
R
ec
o
g
n
itio
n
If
it
f
in
d
s
a
n
y
b
a
r
r
ier
t
h
en
it
c
an
an
aly
s
e
wh
ich
k
in
d
of
b
ar
r
ier
is
it,
if
it
is
non
-
h
u
m
an
,
it
is
m
o
v
in
g
b
ac
k
war
d
.
‑
Step
3:
C
o
m
p
u
tatio
n
W
h
en
it
is
h
u
m
an
,
it
r
e
d
u
ce
s
its
s
p
ee
d
an
d
ch
ec
k
s
th
e
r
is
k
f
ac
to
r
of
its
in
ter
ac
tio
n
.
‑
Step
4:
R
ec
o
n
ciliatio
n
T
h
e
r
o
b
o
t
r
ed
u
ce
s
its
s
p
ee
d
an
d
s
to
p
s
f
o
r
a
wh
ile
wh
e
n
th
e
in
ter
ac
tio
n
is
not
s
af
e,
but
if
th
e
in
ter
ac
tio
n
is
s
af
e,
th
en
it
g
o
es
on.
‑
Step
5:
C
o
m
p
letio
n
At
th
e
en
d
of
th
e
d
ay
,
th
is
alg
o
r
ith
m
test
s
th
e
s
tu
d
y
tar
g
et,
if
th
e
alg
o
r
ith
m
d
o
es
not
ac
h
ie
v
e
th
e
g
o
al,
but
if
it
ac
h
iev
es
th
e
g
o
al,
th
e
alg
o
r
ith
m
will
go
s
m
o
o
th
ly
.
Fig
u
r
e
1.
Sy
s
tem
o
v
er
v
iew
f
o
r
HR
I
Fig
u
r
e
2.
State
d
iag
r
am
of
s
af
ety
f
o
r
h
u
m
a
n
an
d
r
o
b
o
t
in
ter
a
ctio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
3
0
0
–
310
304
Fig
u
r
e
3.
T
h
e
alg
o
r
ith
m
of
th
e
p
r
o
p
o
s
ed
s
im
u
latio
n
p
r
o
ce
s
s
4.
P
AT
H
P
L
ANN
I
NG
AND
A
NALYS
I
S
Saf
ety
p
ath
p
lan
n
i
n
g
is
a
v
ital
co
m
p
o
n
e
n
t
o
f
a
s
tab
le
p
o
licy
o
v
er
all
f
o
r
h
u
m
a
n
-
r
o
b
o
t
in
ter
ac
tio
n
.
B
y
h
av
in
g
s
af
ety
cr
iter
ia
at
th
e
p
lan
n
in
g
le
v
el,
th
e
r
o
b
o
t
ca
n
b
e
b
etter
r
esp
o
n
d
to
u
n
ex
p
ec
te
d
s
af
ety
in
ci
d
en
ts
.
Plan
n
in
g
is
u
s
ed
to
im
p
r
o
v
e
co
n
tr
o
l
o
u
tco
m
es
b
y
u
s
in
g
a
s
m
o
o
th
r
o
u
te
d
esig
n
[
2
5
,
2
6
]
t
o
e
n
h
an
c
e
m
o
n
ito
r
in
g
.
A
s
im
ilar
s
tr
ateg
y
is
ad
o
p
ted
to
r
ep
licate
th
e
o
u
tco
m
e
[
2
7
,
2
8
]
.
Nev
er
th
ele
s
s
,
th
e
p
o
ten
tial
r
is
k
cr
iter
ia
ar
e
d
e
f
in
ed
an
d
ev
al
u
ated
u
s
in
g
th
e
p
r
o
p
o
s
ed
m
eth
o
d
o
f
m
o
tio
n
p
lan
n
in
g
[
2
9
,
3
0
]
.
I
n
d
e
cid
in
g
h
az
ar
d
s
,
th
at
cr
iter
ia
ex
p
licitly
co
n
s
id
er
th
e
in
er
tia
m
an
ip
u
l
ato
r
o
f
th
e
u
s
er
an
d
th
e
m
ass
ce
n
ter
.
A
two
-
s
tag
e
p
lan
n
in
g
s
tr
ateg
y
is
in
ten
d
ed
t
o
r
eso
lv
e
p
o
ten
tial
co
n
f
lictin
g
p
lan
n
in
g
cr
iter
ia.
T
h
e
p
r
o
p
o
s
ed
p
lan
is
test
ed
in
a
s
im
u
latio
n
to
co
m
p
ar
e
th
e
p
ar
am
eter
s
an
d
s
h
o
w
t
h
eir
o
u
t
p
u
t in
a
r
ea
l
-
tim
e
s
ce
n
ar
i
o
.
4
.
1
.
Appro
a
ch
T
h
is
r
esear
ch
was
ap
p
lied
to
s
p
ac
e
p
lan
n
in
g
f
o
r
th
e
co
b
o
t
m
o
v
em
en
t.
By
ch
o
o
s
in
g
s
af
er
co
n
f
ig
u
r
atio
n
s
at
th
e
p
lan
n
i
n
g
lev
el,
p
o
s
s
ib
le
h
az
a
r
d
s
can
be
av
o
id
e
d
.
Fig
u
r
e
4
illu
s
tr
ates
HR
I
in
a
d
i
f
f
er
en
t
p
o
s
itio
n
in
a
s
im
u
lated
en
v
i
r
o
n
m
en
t,
an
d
th
e
c
o
m
p
u
tatio
n
al
lo
ad
f
o
r
h
az
ar
d
r
esp
o
n
s
e
d
u
r
in
g
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
can
be
r
ed
u
ce
d
.
T
h
e
co
b
o
t
h
as
th
e
s
am
e
en
d
-
ef
f
ec
to
r
lo
ca
tio
n
in
b
o
th
p
an
els.
Saf
e
p
r
ep
a
r
atio
n
is
an
ess
en
tial
p
ar
t
o
f
th
e
Secu
r
ity
Stra
teg
y
.
Fo
r
ex
am
p
le,
if
th
e
p
ath
to
f
o
llo
w
is
d
esig
n
ed
u
s
in
g
a
g
e
n
er
al
p
at
h
p
lan
n
i
n
g
p
r
o
ce
s
s
,
th
e
r
o
b
o
t
will
s
p
en
d
m
o
s
t
o
f
its
co
n
f
i
g
u
r
atio
n
s
with
h
ig
h
in
er
tia.
W
h
en
th
e
c
o
n
s
u
m
er
u
n
ex
p
ec
ted
ly
m
o
v
es
clo
s
er
to
t
h
e
r
o
b
o
t,
th
e
p
o
s
s
ib
le
im
p
a
ct
f
o
r
ce
o
f
th
e
co
llis
io
n
wo
u
ld
b
e
m
u
c
h
h
i
g
h
er
t
h
an
if
th
e
r
o
b
o
t
h
a
d
b
ee
n
in
a
lo
w
in
er
tia
s
ettin
g
,
r
eg
a
r
d
less
o
f
th
e
r
ea
l
-
tim
e
co
n
tr
o
ller
u
s
ed
to
d
ea
l w
ith
p
o
ten
tial im
p
ac
t in
cid
en
ts
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2089
-
4
8
5
6
A
s
imu
la
ted
r
is
k
a
s
s
es
s
men
t
of
h
u
ma
n
-
r
o
b
o
t
in
tera
ctio
n
in
th
e
d
o
mestic
en
viro
n
men
t
(
Ta
m
a
n
n
a
E
K
a
o
n
a
i
n
)
305
Fig
u
r
e
5
illu
s
tr
ates
th
e
s
im
u
latio
n
of
an
ar
m
r
o
b
o
t
w
h
ich
ca
lls
as
an
ag
en
t,
an
d
Fig
u
r
e
6
d
is
p
lay
s
all
th
e
jo
in
ts
of
an
ar
m
r
o
b
o
t.
T
h
e
ar
m
r
o
b
o
t
h
as
s
p
ec
if
ied
,
r
ewa
r
d
ed
f
r
o
m
th
e
f
i
g
u
r
e
d
ep
en
d
i
n
g
on
th
e
en
v
ir
o
n
m
en
t,
an
d
th
e
ag
e
n
t
tak
es
th
e
r
eq
u
ir
ed
ac
tio
n
an
d
d
i
s
cu
s
s
es
b
r
ief
ly
b
elo
w.
Her
e,
th
e
en
v
ir
o
n
m
en
t
is
wh
er
e
th
e
two
ar
m
jo
in
ts
ar
e
in
s
p
ac
e.
T
h
e
r
ewa
r
d
is
th
e
n
eg
ativ
e
of
th
e
f
in
g
e
r
to
g
o
al
d
if
f
er
en
ce
.
T
h
e
ac
tio
n
s
co
n
s
is
t
of
a
s
p
ec
if
ic
m
o
v
em
en
t
u
p
war
d
s
or
d
o
wn
war
d
s
on
one
of
th
e
two
jo
in
ts
.
State
f
o
r
ce
lifts
th
e
cu
p
,
h
o
ld
s
a
cu
p
,
lo
wer
cu
p
u
s
ed
f
o
r
d
ef
en
s
e
ac
tiv
atio
n
.
Fig
u
r
e
4
.
A
s
im
u
lated
HR
I
Fig
u
r
e
5
.
Simu
lated
a
r
m
r
o
b
o
t
Fig
u
r
e
6
.
J
o
in
ts
of
ar
m
r
o
b
o
t
4
.
2
.
K
inem
a
t
ics
m
o
del
f
o
r
t
he
s
ev
en‐
DO
F
of
an
a
rm
r
o
bo
t
T
h
e
k
in
e
m
atics
m
o
d
el
f
o
r
th
e
7
‐
DOF
co
n
s
is
ts
of
s
ev
e
n
d
eg
r
ee
s
of
f
r
ee
d
o
m
of
an
a
r
m
r
o
b
o
t
in
Fig
u
r
e
7
an
d
th
e
s
ch
em
atic
d
i
ag
r
am
s
h
o
wn
in
Fig
u
r
e
8
.
T
h
e
s
ev
en
-
DOF
m
o
d
els
an
d
ea
c
h
jo
in
t
ar
e
r
o
tatin
g
.
T
h
e
b
lo
ck
d
ia
g
r
am
of
a
s
ev
en
-
d
eg
r
ee
r
ea
l
DOF
m
o
d
el
is
p
r
esen
ted
in
Fig
u
r
e
7
.
C
o
o
r
d
in
ate
f
r
a
m
es
ar
e
ass
ig
n
ed
f
o
r
th
is
7
‐
DOF
(
Fra
m
e
0
to
Fra
m
e
7
)
.
1
a
n
d
an
y
jo
in
t
ax
is
p
er
p
en
d
icu
lar
to
th
e
p
lan
e
is
o
r
ien
te
d
.
Fra
m
e
0
is
s
et
to
b
ase
an
d
alig
n
s
with
f
r
am
e
1,
wh
er
e
th
e
in
itial
jo
in
ts
of
±1
ar
e
0
an
d
f
r
am
e
E
is
th
e
en
d
ef
f
ec
to
r
f
r
am
e.
Fra
m
e
0
is
th
e
r
ef
er
en
ce
f
r
a
m
e.
T
a
b
le
1
s
h
o
ws
th
e
co
r
r
esp
o
n
d
in
g
lin
k
p
ar
am
eter
s
f
o
r
th
e
7
-
DOF
ar
m
.
E
ac
h
k
n
o
wn
h
o
m
o
g
en
o
u
s
tr
an
s
f
o
r
m
atio
n
De
n
av
it
–
Har
ten
b
e
r
g
m
atr
i
x
−
1
[
3
1
,
3
2
]
can
be
d
er
iv
ed
f
r
o
m
th
e
tr
an
s
f
o
r
m
atio
n
m
atr
ix
of
th
e
7
-
DOF
ar
m
m
o
d
el.
Ob
tain
in
g
th
e
p
lace
v
ec
to
r
th
r
o
u
g
h
th
e
f
o
r
war
d
k
in
em
atics
will
not
be
h
ar
d
.
T
ab
le
1.
L
in
k
p
ar
a
m
eter
s
of
th
e
7
‐
d
o
f
m
o
d
el
F
r
a
me
Li
n
k
i
−
1
a
i
−
1
d
i
q
i
q
m
i
n
q
m
a
x
0
‐
1
1
0
0
d
1
q
1
‐
2
7
0
2
7
0
1
‐
2
2
‐
9
0
0
0
q
2
‐
1
1
0
1
1
0
2
‐
3
3
9
0
0
d
3
q
3
‐
1
8
0
1
8
0
3
‐
4
4
‐
9
0
0
0
q
4
‐
1
1
0
1
1
0
4
‐
5
5
9
0
0
d
5
q
5
‐
1
8
0
1
8
0
5
‐
6
6
‐
9
0
0
0
q
6
‐
9
0
90
6
‐
7
7
9
0
0
0
q
7
‐
2
7
0
2
7
0
7
‐
E
En
d
0
0
d
7
0
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
3
0
0
–
310
306
Fig
u
r
e
7.
T
h
e
k
in
e
m
atics
m
o
d
el
of
s
ev
en
‐
DOF
of
an
ar
m
r
o
b
o
t
Fig
u
r
e
8.
Sch
em
atic
d
iag
r
am
of
s
ev
en
‐
DOF
of
an
ar
m
r
o
b
o
t
4
.
2
.
1
.
I
nv
er
s
e
K
inem
a
t
ics
A
wid
esp
r
ea
d
r
ev
er
s
e
of
J
ac
o
b
ian
m
atr
ix
,
p
s
eu
d
o
in
v
er
s
e
†
=
(
)
−
1
is
wid
ely
u
s
ed
f
o
r
a
r
o
b
o
t
an
d
its
d
r
awb
ac
k
is
th
at
th
e
p
s
eu
d
o
in
v
er
s
e
o
f
te
n
lead
s
th
e
r
o
b
o
t
in
to
s
in
g
u
la
r
ities
[
3
3
]
.
A
n
o
th
er
g
e
n
er
alize
d
r
ev
er
s
e
is
th
e
in
er
tia−w
eig
h
te
d
p
s
eu
d
o
i
n
v
er
s
e
†
=
−
1
(
−
1
)
−
1
a
s
o
r
t
of
s
o
lv
ed
m
o
tio
n
r
ate
co
n
tr
o
l
tech
n
iq
u
e
p
r
o
p
o
s
ed
in
wo
r
k
[
3
4
]
,
wh
ich
is
u
s
ed
to
m
in
im
ize
en
er
g
y
by
u
s
in
g
th
e
in
er
tia
m
atr
ix
as
th
e
weig
h
tin
g
m
atr
ix
.
T
h
is
will
m
ea
s
u
r
e
wh
at
each
jo
in
t
v
ar
ia
b
le
will
be
if
we
wan
t
th
e
h
a
n
d
to
be
p
lace
d
at
a
p
ar
ticu
lar
p
o
in
t
a
n
d
h
av
e
a
s
p
ec
if
ic
lo
ca
tio
n
.
T
h
e
e
n
d
ef
f
ec
t
o
r
’
s
lo
ca
tio
n
an
d
o
r
ien
tatio
n
r
elativ
e
to
th
e
b
ase
f
r
am
e,
m
ea
s
u
r
e
all
p
o
s
s
ib
le
jo
in
t
an
g
le
s
ets
an
d
lin
k
g
eo
m
et
r
ies
to
u
s
e
Ac
h
iev
e
a
g
i
v
en
e
n
d
ef
f
ec
t
o
r
p
o
s
itio
n
an
d
o
r
ie
n
tatio
n
[
3
5
,
3
6
]
.
T
h
e
in
v
er
s
e
k
in
em
atics
s
o
lu
tio
n
f
o
r
th
e
clo
s
ed
‐
lo
o
p
d
escr
ib
es
h
er
e.
Su
p
p
o
s
e
a
task
s
p
ac
e
tr
ajec
to
r
y
(
(
)
,
(
)
)
̇
is
g
iv
en
,
an
d
th
e
o
b
jectiv
e
is
to
f
in
d
a
f
ea
s
ib
le
j
o
in
t
s
p
ac
e
tr
ajec
to
r
y
(
(
)
,
(
)
)
̇
th
at
r
ep
r
o
d
u
ce
s
th
e
tr
ajec
to
r
y
g
iv
e
n
.
T
h
e
d
if
f
er
en
tial
k
in
em
atics
eq
u
atio
n
estab
lis
h
es
a
lin
ea
r
m
ap
p
i
n
g
b
etwe
en
c
o
m
m
o
n
s
p
ac
e
v
elo
cities
an
d
task
s
p
ac
e
v
elo
cities,
in
ter
m
s
of
eith
er
th
e
g
eo
m
etr
ic
or
th
e
an
aly
tic
al
J
ac
o
b
ian
an
d
can
be
u
s
ed
to
s
o
lv
e
jo
in
t
v
elo
cities
u
s
in
g
k
in
em
atic
e
q
u
atio
n
.
T
h
en
th
e
e
q
u
atio
n
f
o
r
d
if
f
er
en
tial
k
in
em
atics
tak
es
th
e
f
o
r
m
as
f
o
llo
ws:
̇
=
(
)
̇
(
1
)
T
h
e
s
im
p
le
r
e
v
er
s
e
s
o
lu
tio
n
to
(
1
)
can
be
o
b
tain
e
d
by
u
s
in
g
th
e
p
s
eu
d
o
in
v
er
s
e
†
of
t
h
e
m
atr
ix
J
d
u
e
to
th
e
n
o
n
‐
s
q
u
a
r
e
J
ac
o
b
ian
m
atr
ix
f
o
r
s
ev
en
‐
DOF
m
o
d
el
a
n
d
t
an
d
th
e
r
ev
er
s
e
s
o
lu
tio
n
can
be
wr
itten
as
f
o
llo
ws
:
̇
=
†
(
)
̇
(
2
)
wh
er
e
th
e
p
s
eu
d
o
in
v
er
s
e
†
ca
n
b
e
co
m
p
u
ted
as
†
=
(
)
−
1
Fo
r
a
k
i
n
em
atics
s
ev
en
‐
DOF
m
o
d
el,
a
n
o
n
em
p
ty
n
u
ll
s
p
ac
e
ex
is
ts
d
u
e
to
th
e
ex
ce
s
s
o
f
in
p
u
t
s
p
ac
e
r
elativ
e
to
s
p
ac
e
>
,
wh
ich
is
av
ailab
le
to
s
et
u
p
s
y
s
tem
atic
p
r
o
ce
d
u
r
es f
o
r
e
f
f
ec
tiv
e
h
an
d
lin
g
o
f
DOFs
[
37
,
38
]
.
T
h
e
n
u
ll
s
p
ac
e
is
a
s
et
o
f
ta
s
k
s
p
ac
e
s
p
ee
d
s
th
at
g
en
er
at
e
n
u
ll
jo
i
n
t
s
p
ac
e
s
p
ee
d
s
in
t
h
e
cu
r
r
en
t
co
n
f
ig
u
r
atio
n
o
f
th
e
r
o
b
o
t,
a
n
d
th
ese
task
s
p
ee
d
s
ar
e
p
ar
t
o
f
th
e
o
r
th
o
g
o
n
al
c
o
m
p
lem
e
n
t
to
th
e
v
ia
b
le
task
s
p
ac
e
s
p
ee
d
.
A
c
o
m
m
o
n
m
eth
o
d
of
in
clu
d
in
g
th
e
n
u
ll
s
p
ac
e
in
a
s
o
lu
tio
n
is
th
e
f
o
r
m
u
latio
n
in
[
h
]
,
̇
=
†
̇
+
(
−
†
)
,
wh
er
e
z
R
n
.
T
h
e
f
ir
s
t
ter
m
is
a
p
ar
ticu
lar
s
o
lu
tio
n
to
th
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v
er
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r
o
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lem
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d
th
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o
n
d
ter
m
r
ep
r
esen
ts
th
e
h
o
m
o
g
e
n
e
o
u
s
s
o
lu
tio
n
to
th
e
p
r
o
b
lem
̇
=
0
.
T
h
u
s
,
th
e
g
en
er
al
in
v
e
r
s
e
s
o
lu
tio
n
can
be
wr
itten
as
:
̇
=
†
(
)
̇
+
(
−
†
(
)
(
)
)
0
̇
(
3
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2089
-
4
8
5
6
A
s
imu
la
ted
r
is
k
a
s
s
es
s
men
t
of
h
u
ma
n
-
r
o
b
o
t
in
tera
ctio
n
in
th
e
d
o
mestic
en
viro
n
men
t
(
Ta
m
a
n
n
a
E
K
a
o
n
a
i
n
)
307
wh
er
e
th
e
m
atr
ix
(
−
†
(
)
(
)
)
is
a
p
r
o
jecto
r
of
th
e
j
o
in
t
v
ec
to
r
0
̇
o
n
to
N
(
J)
.
Sin
ce
n
u
m
er
ical
in
te
g
r
atio
n
,
o
p
en
-
lo
o
p
s
o
lu
tio
n
s
with
jo
in
t
v
ar
iab
les
ev
en
tu
ally
lead
to
s
o
lu
tio
n
s
th
at
d
r
if
t
an
d
th
en
wo
r
k
p
lace
m
is
tak
es
to
s
o
lv
e
th
ese
d
is
ad
v
an
tag
es.
4
.
2
.
2
.
F
o
rwa
rd
k
inem
a
t
ics
T
h
e
f
o
r
war
d
k
i
n
em
atic
asp
ec
t
is
th
at,
to
g
eth
er
with
all
th
e
in
f
o
r
m
atio
n
on
jo
in
ts
of
th
e
ar
ticu
lated
m
o
d
el,
ce
r
tain
p
ar
ts
of
th
e
m
o
d
el
ar
e
co
m
p
u
te
d
at
a
s
p
ec
if
ic
tim
e
f
r
o
m
th
e
p
o
s
itio
n
an
d
o
r
ien
tatio
n
of
th
e
o
b
ject.
T
h
e
p
o
s
itio
n
of
th
e
th
u
m
b
en
d
will
be
d
eter
m
in
e
d
f
r
o
m
th
e
an
g
le
of
th
e
s
h
o
u
l
d
er
,
elb
o
w,
wr
is
t,
p
alm
,
an
d
k
n
u
ck
le
jo
i
n
ts
,
if
th
e
o
b
j
ec
t
to
b
e
an
im
ate
d
is
an
ar
m
with
th
e
s
h
o
u
ld
er
r
em
ain
in
g
o
n
a
f
i
x
ed
p
o
s
itio
n
.
T
h
r
ee
of
th
ese
jo
i
n
ts
—
th
e
s
h
o
u
ld
er
,
wr
is
t,
a
n
d
b
ase
of
th
e
t
h
u
m
b
—
ar
e
f
r
ee
to
a
g
r
ea
ter
th
an
one
d
e
g
r
ee
.
T
h
e
p
o
s
itio
n
of
th
e
s
h
o
u
ld
e
r
wo
u
l
d
also
be
d
eter
m
i
n
ed
f
r
o
m
a
n
o
th
er
m
o
d
el
ch
a
r
ac
ter
is
tics
,
if
th
e
m
o
d
el
was
a
h
u
m
an
b
ein
g
in
its
en
tire
ty
[
3
9
,
4
0
]
.
T
h
e
f
o
r
war
d
k
in
e
m
atics
s
o
lu
tio
n
is
g
iv
en
b
elo
w
[
4
1
]
.
=
−
1
(
(
5
+
7
6
)
3
4
+
7
(
4
5
3
+
3
5
)
6
)
+
1
(
2
(
3
+
4
(
5
+
7
6
)
−
7
5
4
6
)
+
2
(
3
(
5
+
7
6
)
4
+
7
(
3
4
5
−
3
5
)
6
)
)
;
=
1
(
(
5
+
7
6
)
3
4
+
7
(
4
5
3
+
3
5
)
6
)
+
1
(
2
(
3
+
4
(
5
+
7
6
)
−
7
5
4
6
)
+
2
(
3
(
5
+
7
6
)
4
+
7
(
3
4
5
−
3
5
)
6
)
)
;
=
1
+
7
2
3
5
6
−
3
2
(
(
5
+
7
6
)
4
+
7
4
5
6
)
+
2
(
3
+
4
(
5
+
7
6
)
−
7
5
4
6
)
4
.
3
.
Sim
ula
t
io
n
a
s
s
ess
m
ent
A
s
im
u
latio
n
en
v
ir
o
n
m
e
n
t
wa
s
d
ev
elo
p
ed
to
e
v
alu
ate
v
ar
io
u
s
co
b
o
t
ar
ch
itectu
r
es
f
o
r
t
h
e
p
lan
n
in
g
alg
o
r
ith
m
s
.
T
h
e
co
b
o
ts
ar
e
m
o
d
eled
in
a
d
o
m
esti
c
ar
ea
by
s
im
u
lated
o
n
lin
e
s
o
f
twar
e.
Fig
u
r
e
9
s
h
o
ws
th
e
ex
p
ec
ted
m
o
v
e
m
en
t
of
a
3
-
lin
k
p
lan
ar
r
o
b
o
t
u
s
in
g
th
e
b
asic
alg
o
r
ith
m
,
with
th
e
s
u
m
-
b
ased
h
az
ar
d
cr
iter
io
n
.
T
h
e
co
b
o
t
aim
s
to
r
ed
u
ce
th
e
s
p
ee
d
af
ter
d
etec
tin
g
th
e
le
v
el
of
d
an
g
er
d
u
r
in
g
th
e
i
n
ter
ac
tio
n
.
T
h
e
s
am
e
f
u
n
ctio
n
is
s
h
o
wn
as
ex
p
ec
te
d
by
th
e
h
az
a
r
d
cr
iter
ia
b
ased
on
th
e
co
m
m
o
d
ity
in
Fig
u
r
e
10
wh
en
th
e
h
u
m
an
is
in
a
b
ac
k
war
d
p
o
s
itio
n
.
I
n
b
o
th
ca
s
es,
o
n
ly
tar
g
et
an
d
h
az
a
r
d
cr
iter
io
n
co
s
t
f
u
n
ctio
n
s
ar
e
u
s
ed
to
e
x
p
lain
th
e
ef
f
ec
t o
f
th
e
h
az
ar
d
cr
iter
io
n
.
Fig
u
r
es
9
an
d
10
d
em
o
n
s
tr
ate
th
e
d
if
f
er
en
ce
s
b
etwe
en
th
e
two
v
er
s
io
n
s
of
th
e
h
az
ar
d
cr
it
er
io
n
.
T
h
e
s
u
m
-
b
ased
h
az
ar
d
cr
iter
io
n
m
ea
n
s
th
at
th
e
h
az
ar
d
-
i
n
f
lu
en
ci
n
g
v
ar
iab
les
s
h
o
u
ld
be
v
iewe
d
s
ep
ar
ately
wh
en
d
eter
m
in
in
g
h
az
ar
d
r
ates.
On
e
b
en
ef
it
of
th
e
s
u
m
-
b
ased
cr
ite
r
io
n
is
th
at
th
e
d
ef
in
itio
n
is
s
im
ilar
an
d
d
is
tan
ce
-
b
ased
to
o
t
h
er
q
u
ad
r
atic
c
o
s
t
f
u
n
ctio
n
s
c
o
m
m
o
n
ly
u
s
ed
in
th
e
p
o
ten
tial
f
ield
m
et
h
o
d.
In
t
h
is
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
,
th
e
co
b
o
t
is
u
n
ab
le
to
lo
ca
te
an
o
b
s
tacle
.
It
s
h
o
u
ld
d
eter
m
in
e
wh
at
k
in
d
of
h
u
r
d
le
if
it
is
h
u
m
a
n
,
th
e
r
o
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:
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test
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r
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I
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Dete
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ally
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ased
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on
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o
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ca
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I
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J
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mestic
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(
Ta
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)
309
RE
F
E
R
E
NC
E
S
[1
]
P.
I.
C
o
rk
e
,
“
S
a
fe
ty
of
a
d
v
a
n
c
e
d
ro
b
o
ts
in
h
u
m
a
n
e
n
v
ir
o
n
m
e
n
t
s.
A
d
isc
u
ss
io
n
p
a
p
e
r
fo
r
IARP,
”
In
ter
n
a
ti
o
n
a
l
Ad
v
a
n
c
e
d
Ro
b
o
t
ics
Pro
g
r
a
mm
e
,
1
9
9
9
.
[2
]
C.
W.
Lee
,
et
al
.
,
“
Re
p
o
rt
on
t
h
e
F
irst
IART/IE
EE
-
RAS
Jo
in
t
Wo
rk
s
h
o
p
:
Tec
h
n
ica
l
C
h
a
ll
e
n
g
e
fo
r
De
p
e
n
d
a
b
le
Ro
b
o
ts
in
Hu
m
a
n
E
n
v
ir
o
n
m
e
n
ts,
”
IART/IE
EE
-
RAS
,
2
0
0
1
.
[3
]
S
o
n
y
Ori
o
,
On
li
n
e
:
h
tt
p
:/
/www
.
so
n
v
.
n
e
t/
S
o
n
v
In
f
o
/QRIO/tec
h
n
o
lo
g
v
/i
n
d
e
x
5
.
h
tml.
[4
]
C.
Ha
rp
e
r
a
n
d
G.
Virk
,
“
To
w
a
rd
s
th
e
De
v
e
lo
p
m
e
n
t
of
I
n
tern
a
ti
o
n
a
l
S
a
fe
ty
S
tan
d
a
rd
s
fo
r
Hu
m
a
n
Ro
b
o
t
In
tera
c
ti
o
n
,
”
I
n
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
of
S
o
c
i
a
l
R
o
b
o
ti
c
s
,
v
o
l
.
2,
n
o
.
3,
pp.
2
2
9
–
2
3
4
,
2
0
1
0
.
[5
]
Ame
ric
a
n
Na
t
io
n
a
l
S
t
a
n
d
a
r
d
f
o
r
In
d
u
stria
l
Ro
b
o
ts
a
n
d
Ro
b
o
t
S
y
st
e
ms
-
S
a
fety
Req
u
ire
me
n
ts
,
RIA/
AN
S
I
R1
5
.
0
6
,
Am
e
rica
n
Na
ti
o
n
a
l
S
tan
d
a
rd
s
In
st
it
u
te
,
Ne
w
Yo
r
k
,
1
9
9
9
.
[6
]
Y.
Ya
m
a
d
a
,
et
al
.,
“
Hu
m
a
n
-
ro
b
o
t
c
o
n
tac
t
in
th
e
sa
fe
g
u
a
r
d
in
g
sp
a
c
e
,
”
IEE
E/
AS
M
E
T
ra
n
sa
c
ti
o
n
s
on
M
e
c
h
a
tro
n
ics
,
v
o
l.
2,
n
o
.
4,
pp.
2
3
0
-
2
3
6
,
1
9
9
7
.
[7
]
F.
J.
R.
Lera
,
et
al
.
,
“
Cy
b
e
rse
c
u
rit
y
of
Ro
b
o
ti
c
s
a
n
d
Au
t
o
n
o
m
o
u
s
S
y
ste
m
s:
P
riv
a
c
y
a
n
d
S
a
fe
ty
,
”
R
o
b
o
ti
c
s
-
L
e
g
a
l
,
Et
h
ica
l
a
n
d
S
o
c
i
o
e
c
o
n
o
mic
Imp
a
c
ts
,
2
0
1
7
.
[8
]
T.
B
o
n
a
c
i,
et
al
.
,
“
To
M
a
k
e
a
Ro
b
o
t
S
e
c
u
re
:
An
Ex
p
e
rime
n
t
a
l
An
a
ly
sis
of
Cy
b
e
r
S
e
c
u
r
it
y
Th
re
a
ts
Ag
a
in
st
Tele
o
p
e
ra
ted
S
u
rg
ica
l
R
o
b
o
ts,
”
a
rXiv
p
re
p
r
in
t
a
rXiv
:1
5
0
4
.
0
4
3
3
9
,
2
0
1
5
.
[9
]
R.
Ola
wo
y
i
n
,
“
S
a
fe
t
y
a
n
d
Au
t
o
m
a
ti
o
n
of
C
o
ll
a
b
o
ra
ti
v
e
Ro
b
o
t
S
y
ste
m
in
W
o
rk
En
v
ir
o
n
m
e
n
t,
”
Ro
b
o
t
ics
&
Au
to
m
a
ti
o
n
E
n
g
in
e
e
rin
g
J
o
u
r
n
a
l
,
v
o
l
.
3,
n
o
.
3,
2
0
1
8
,
d
o
i
:
1
0
.
1
9
0
8
0
/
RAEJ.2
0
1
8
.
0
3
.
5
5
5
6
1
3
.
[1
0
]
U.
Do
m
b
ro
ws
k
i,
T.
S
tefa
n
a
k
,
a
n
d
A.
Re
ime
r,
“
S
imu
lati
o
n
of
h
u
m
a
n
-
ro
b
o
t
c
o
ll
a
b
o
ra
ti
o
n
by
m
e
a
n
s
of
p
o
we
r
a
n
d
fo
rc
e
li
m
it
in
g
,
”
Pro
c
e
d
i
a
M
a
n
u
f
a
c
tu
rin
g
,
v
o
l.
1
7
,
p
p
.
1
3
4
–
1
4
1
,
2
0
1
8
.
[1
1
]
R.
Weitsc
h
a
t
a
n
d
H.
As
c
h
e
m
a
n
n
,
“
S
a
fe
a
n
d
Eff
icie
n
t
Hu
m
a
n
–
Ro
b
o
t
Co
ll
a
b
o
ra
ti
o
n
P
a
rt
II
:
Op
ti
m
a
l
G
e
n
e
ra
li
z
e
d
Hu
m
a
n
-
in
-
t
h
e
-
Lo
o
p
Re
a
l
-
Ti
m
e
M
o
ti
o
n
G
e
n
e
ra
ti
o
n
,
”
IEE
E
Ro
b
o
ti
c
s
a
n
d
Au
t
o
ma
t
io
n
L
e
tt
e
rs
,
v
o
l.
3,
n
o
.
4,
pp.
3
7
8
1
-
3
7
8
8
,
2
0
1
8
.
[1
2
]
G.
Lo
u
k
a
s,
et
al
.,
“
Clo
u
d
-
Ba
se
d
Cy
b
e
r
-
P
h
y
sic
a
l
I
n
tru
si
o
n
De
tec
t
io
n
f
o
r
Ve
h
icle
s
Us
in
g
De
e
p
Le
a
rn
in
g
,
”
IEE
E
Acc
e
ss
,
v
o
l.
6,
pp.
3
4
9
1
-
3
5
0
8
,
2
0
1
8
.
[1
3
]
V.
Ba
tso
n
,
T.
Lo
u
is
,
D.
R.
Wi
m
m
e
r
Jr,
“
Un
m
a
n
n
e
d
Tac
ti
c
a
l
Au
to
n
o
m
o
u
s
C
o
n
tr
o
l
a
n
d
Co
l
lab
o
ra
t
io
n
T
h
re
a
t
a
n
d
Vu
ln
e
ra
b
il
i
ty
As
se
ss
m
e
n
t,
”
P
h
D
Th
e
sis,
Na
v
a
l
P
o
stg
ra
d
u
a
te
S
c
h
o
o
l,
M
o
n
tere
y
,
Ca
li
f
o
rn
ia,
2
0
1
5
.
[1
4
]
A.
Jo
n
e
s
a
n
d
J.
S
trau
b
,
“
Us
in
g
d
e
e
p
lea
rn
in
g
to
d
e
tec
t
n
e
two
rk
in
tru
si
o
n
s
a
n
d
m
a
lwa
re
in
a
u
to
n
o
m
o
u
s
ro
b
o
ts,
”
Cy
b
e
r
S
e
n
sin
g
2
0
1
7
,
2
0
1
7
.
[1
5
]
T.
Vu
o
n
g
,
“
Cy
b
e
r
-
p
h
y
sic
a
l
In
tr
u
s
io
n
De
tec
ti
o
n
f
o
r
Ro
b
o
ti
c
Ve
h
icle
s,
”
P
h
D
T
h
e
sis,
Un
i
v
e
rsity
of
G
re
e
n
wic
h
,
2
0
1
7
.
[1
6
]
S.
De
m
ir
a
n
d
A.
Du
rd
u
,
“
Hu
m
a
n
Ro
b
o
t
In
tera
c
ti
o
n
in
I
n
d
o
o
r
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
of
En
g
in
e
e
ri
n
g
S
c
ien
c
e
a
n
d
Co
mp
u
t
in
g
,
v
o
l
.
9,
n
o
.
6,
pp.
2
2
9
6
3
–
2
2
9
6
6
,
2
0
1
9
.
[1
7
]
S
.
Ku
m
a
r,
K
.
Ra
n
i
,
a
n
d
V.
K.
Ba
n
g
a
,
“
Ro
b
o
ti
c
Arm
M
o
v
e
m
e
n
t
Op
t
imiz
a
ti
o
n
Us
i
n
g
S
o
ft
C
o
m
p
u
ti
n
g
,
”
IA
E
S
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
of
R
o
b
o
ti
c
s
and
A
u
t
o
ma
ti
o
n
(IJ
RA
)
,
v
o
l.
6,
n
o
.
1,
p
p
.
1
-
1
4
,
2
0
1
7
,
doi
:
1
0
.
1
1
5
9
1
/i
jra.v
6
i
1
.
p
p
1
-
14.
[1
8
]
A
.
El
S
h
e
n
a
wy
,
K
.
M
o
h
a
m
e
d
,
a
n
d
H
.
M.
Ha
rb
,
“
Ex
p
lo
ra
ti
o
n
S
tr
a
teg
ies
of
Co
o
rd
i
n
a
ted
M
u
lt
i
-
R
o
b
o
t
S
y
ste
m
:
A
Co
m
p
a
ra
ti
v
e
S
tu
d
y
,
”
IAE
S
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
of
R
o
b
o
ti
c
s
a
n
d
A
u
to
ma
ti
o
n
(IJ
RA
)
,
v
o
l.
7,
n
o
.
1
,
p
p
.
48
-
58
,
2
0
1
8
,
doi
:
1
0
.
1
1
5
9
1
/
ij
ra
.
v
7
i1
.
p
p
4
8
-
5
8
.
[1
9
]
S
.
K
.
De
b
n
a
th
,
R
.
Om
a
r,
a
n
d
N
.
B
.
Ab
d
u
l
Lati
p
,
“
Co
m
p
a
riso
n
of
d
iffere
n
t
c
o
n
fi
g
u
ra
ti
o
n
sp
a
c
e
re
p
r
e
se
n
tatio
n
s
f
o
r
p
a
th
p
la
n
n
i
n
g
u
n
d
e
r
c
o
m
b
in
a
t
o
ri
a
l
m
e
th
o
d
,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
of
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
1
4
,
no.
1,
2
0
1
9
,
pp.
1
-
8,
d
o
i:
1
0
.
1
1
5
9
1
/i
jee
c
s.v
1
4
.
i
1
.
p
p
1
-
8.
[2
0
]
R
.
H
.
El
h
a
c
h
e
m
i
Am
a
r,
et
al
.
,
“
Traje
c
to
ry
re
c
o
n
stru
c
ti
o
n
f
o
r
ro
b
o
t
p
ro
g
ra
m
m
in
g
by
d
e
m
o
n
stra
ti
o
n
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
of
E
lec
trica
l
a
n
d
Co
mp
u
ter
E
n
g
i
n
e
e
rin
g
(IJ
ECE
)
,
v
o
l.
1
0
,
n
o
.
3,
p
p
.
3
0
6
6
-
3
0
7
3
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
5
9
1
/i
jec
e
.
v
1
0
i
3
.
p
p
3
0
6
6
-
3
0
7
3
[2
1
]
M.
Attam
imi
a
n
d
T.
Om
o
ri,
“
T
h
e
stu
d
y
of
a
tt
e
n
ti
o
n
e
stim
a
ti
o
n
f
o
r
c
h
il
d
-
ro
b
o
t
i
n
tera
c
ti
o
n
sc
e
n
a
ri
o
s,
”
Bu
ll
e
ti
n
of
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
In
f
o
r
ma
ti
c
s
(BE
EI)
,
v
o
l.
9,
no.
3,
p
p
.
1
2
2
0
–
1
2
2
8
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
5
9
1
/e
e
i.
v
9
i
3
.
2
0
3
5
.
[2
2
]
S
e
lec
ti
n
g
a
d
e
v
e
l
o
p
m
e
n
t
a
p
p
ro
a
c
h
,
Web
Article
,
F
e
b
.
2
0
0
5
.
[O
n
li
n
e
].
A
v
a
il
a
b
le:
h
tt
p
s:/
/www
.
c
m
s.g
o
v
/res
e
a
rc
h
-
sta
ti
stics
-
d
a
ta
-
a
n
d
-
sy
ste
m
s/c
m
sin
fo
rm
a
ti
o
n
-
tec
h
n
o
l
o
g
y
/
x
lc/d
o
wn
l
o
a
d
s/se
lec
ti
n
g
d
e
v
e
l
o
p
m
e
n
tap
p
ro
a
c
h
.
p
d
f
[2
3
]
P.
Va
rley
,
“
Tec
h
n
iq
u
e
s
fo
r
d
e
v
e
lo
p
m
e
n
t
of
sa
fe
ty
-
re
late
d
so
ftwa
re
fo
r
su
r
g
ica
l
ro
b
o
ts
,
”
IEE
E
T
r
a
n
sa
c
ti
o
n
s
on
In
fo
rm
a
t
io
n
T
e
c
h
n
o
l
o
g
y
in
Bi
o
me
d
icin
e
,
v
o
l
.
3,
n
o
.
4,
p
p
.
2
6
1
-
2
6
7
,
1
9
9
9
.
[2
4
]
C.
S
c
h
leg
e
l
,
et
al
.
,
“
Ro
b
o
ti
c
so
f
t
wa
re
sy
ste
m
s:
F
ro
m
c
o
d
e
-
d
riv
e
n
to
m
o
d
e
l
-
d
riv
e
n
d
e
sig
n
s,
”
in
2
0
0
9
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
on
Ad
v
a
n
c
e
d
R
o
b
o
ti
c
s
,
M
u
n
ich
,
2
0
0
9
,
p
p
.
1
-
8
[2
5
]
J.
Be
rg
a
n
d
G.
Re
in
h
a
rt,
“
An
I
n
teg
ra
ted
P
lan
n
i
n
g
a
n
d
P
ro
g
ra
m
m
in
g
S
y
ste
m
fo
r
Hu
m
a
n
-
Ro
b
o
t
-
Co
o
p
e
ra
ti
o
n
,
”
Pro
c
e
d
ia
CIR
P
,
v
o
l
.
6
3
,
p
p
.
95
–
1
0
0
,
2
0
1
7
,
d
o
i:
1
0
.
1
0
1
6
/j
.
p
ro
c
ir
.
2
0
1
7
.
0
3
.
3
1
8
[2
6
]
S.
M
a
c
fa
rlan
e
a
n
d
E.
A.
Cro
ft,
“
Je
rk
-
b
o
u
n
d
e
d
m
a
n
i
p
u
lato
r
traje
c
to
ry
p
la
n
n
i
n
g
:
d
e
si
g
n
fo
r
re
a
l
-
ti
m
e
a
p
p
li
c
a
ti
o
n
s,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
on
Ro
b
o
t
ics
a
n
d
A
u
t
o
ma
ti
o
n
,
v
o
l.
1
9
,
n
o
.
1,
p
p
.
42
-
5
2
,
2
0
0
3
.
[2
7
]
K.
Erk
o
rk
m
a
z
a
n
d
Y.
Alt
in
tas
,
“
Hig
h
s
p
e
e
d
CNC
sy
ste
m
d
e
si
g
n
.
P
a
rt
I:
jerk
li
m
it
e
d
traje
c
to
r
y
g
e
n
e
ra
ti
o
n
a
n
d
q
u
i
n
ti
c
sp
l
in
e
i
n
terp
o
latio
n
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
of
M
a
c
h
i
n
e
T
o
o
ls
a
n
d
M
a
n
u
fa
c
tu
re
,
v
o
l.
41,
no.
9,
p
p
.
1
3
2
3
–
1
3
4
5
,
2
0
0
1
.
[2
8
]
M.
No
k
a
ta,
K.
Ik
u
ta
,
a
n
d
H.
I
sh
ii
,
“
S
a
fe
ty
-
o
p
ti
m
izi
n
g
m
e
th
o
d
of
h
u
m
a
n
-
c
a
re
ro
b
o
t
d
e
sig
n
a
n
d
c
o
n
tr
o
l,
”
in
Pro
c
e
e
d
in
g
s
2
0
0
2
IEE
E
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
on
R
o
b
o
ti
c
s
a
n
d
A
u
to
m
a
ti
o
n
(C
a
t.
N
o
.
0
2
CH3
7
2
9
2
)
,
Was
h
in
g
to
n
,
DC,
USA
,
2
0
0
2
,
p
p
.
1
9
9
1
-
1
9
9
6
.
[2
9
]
A.
Ou
sta
lo
u
p
,
et
al
.
,
“
P
a
th
p
lan
n
i
n
g
by
fra
c
ti
o
n
a
l
d
iffere
n
ti
a
ti
o
n
,
”
Ro
b
o
ti
c
a
,
v
o
l.
2
1
,
n
o
.
1,
p
p
.
59
–
6
9
,
2
0
0
3
.
[3
0
]
O.
Bro
c
k
a
n
d
O.
K
h
a
ti
b
,
“
El
a
st
ic
S
tri
p
s:
A
F
ra
m
e
wo
rk
fo
r
M
o
ti
o
n
G
e
n
e
ra
ti
o
n
in
Hu
m
a
n
En
v
i
ro
n
m
e
n
ts,
”
T
h
e
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
of
R
o
b
o
ti
c
s
Res
e
a
rc
h
,
v
o
l.
2
1
,
n
o
.
1
2
,
p
p
.
1
0
3
1
–
1
0
5
2
,
2
0
0
2
.
[3
1
]
J.
J.
Cra
ig
,
I
n
tro
d
u
c
ti
o
n
to
ro
b
o
ti
c
s:
me
c
h
a
n
ics
a
n
d
c
o
n
tro
l
,
3
rd
e
d
.
Ne
w
Yo
rk
:
P
re
n
ti
c
e
‐Ha
ll
,
2
0
0
5
.
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