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48
~
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pp
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I
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D
UCT
I
O
N
A
m
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-
r
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b
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t s
y
s
te
m
s
(
M
R
S)
is
a
s
e
t o
f
m
o
b
ile
r
o
b
o
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th
a
t
m
a
y
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a
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s
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ca
p
ab
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w
h
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e
y
ar
e
co
n
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ted
th
r
o
u
g
h
a
w
ir
eles
s
s
en
s
o
r
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et
w
o
r
k
to
s
h
ar
e
th
e
s
e
n
s
o
r
y
in
f
o
r
m
a
tio
n
w
it
h
r
ec
o
n
f
i
g
u
r
ab
le
s
e
n
s
i
n
g
ca
p
ab
ilit
ies
[
1
]
.
T
h
e
ess
en
tial
g
o
al
o
f
MR
S
is
to
ac
h
ie
v
e
a
co
m
p
le
te
task
i
n
a
s
h
o
r
ter
ti
m
e
t
h
an
t
h
e
r
eq
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ir
ed
ti
m
e
f
o
r
ac
h
iev
i
n
g
th
e
s
a
m
e
ta
s
k
u
s
i
n
g
a
s
in
g
le
r
o
b
o
t,
s
in
ce
in
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t
h
e
tas
k
is
p
er
f
o
r
m
ed
s
i
m
u
lta
n
eo
u
s
l
y
[
2
]
.
MRS
h
a
s
a
n
u
m
b
er
o
f
ad
v
a
n
tag
e
s
o
v
er
a
s
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n
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le
r
o
b
o
t
s
y
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te
m
s
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c
h
as
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ig
h
er
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au
lt
-
to
ler
an
ce
,
co
n
s
o
lid
atio
n
o
f
th
e
o
v
er
lap
p
ed
in
f
o
r
m
a
tio
n
[
3
,
4
]
,
p
r
o
h
ib
itio
n
o
f
tas
k
ex
ec
u
t
io
n
b
y
o
th
e
r
r
o
b
o
ts
[
5
]
,
[
6
]
,
r
ed
u
ctio
n
o
f
en
er
g
y
co
n
s
u
m
p
tio
n
w
h
ich
lead
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n
g
to
lo
n
g
er
co
m
m
u
n
icatio
n
t
i
m
e
d
u
r
i
n
g
t
h
e
ta
s
k
ac
h
iev
e
m
e
n
t [
7
]
,
[
8
]
.
R
ec
en
t
l
y
M
R
S
h
a
v
e
b
ee
n
u
s
e
d
in
s
ev
er
al
ap
p
licatio
n
s
t
h
at
ar
e
d
an
g
er
o
u
s
to
th
e
h
u
m
an
s
u
ch
as
p
o
s
t
d
is
aster
r
elief
,
m
ilit
ar
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ap
p
licatio
n
s
,
s
ea
r
c
h
an
d
r
escu
e,
s
u
r
v
eilla
n
ce
,
clea
n
i
n
g
,
m
i
n
e
clea
r
in
g
[
9
]
-
[
1
2
]
,
etc.
I
n
s
u
c
h
ap
p
licatio
n
s
r
o
b
o
ts
s
h
o
u
ld
m
ak
e
a
d
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is
io
n
w
h
et
h
e
r
to
s
ea
r
ch
n
e
w
tas
k
s
o
r
est
ab
lis
h
co
o
p
er
ativ
e
in
ter
ac
tio
n
s
to
ac
h
ie
v
e
th
e
ir
in
d
iv
id
u
al
a
n
d
co
llectiv
e
g
o
als [
4
]
,
[
1
3
]
,
[
1
4
]
.
Mo
s
t
o
f
M
R
S
ap
p
licatio
n
s
d
e
p
en
d
p
r
i
m
ar
i
l
y
o
n
t
h
e
e
x
p
lo
r
atio
n
o
f
th
e
e
n
v
ir
o
n
m
en
t
i
n
a
m
i
n
i
m
u
m
ti
m
e,
an
d
t
h
e
m
ap
o
f
t
h
e
en
v
i
r
o
n
m
e
n
t
is
g
en
er
ated
to
f
o
r
m
th
e
MR
S
ex
p
lo
r
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p
r
o
ce
s
s
.
MRS
ex
p
lo
r
atio
n
p
r
o
ce
s
s
en
co
u
n
ter
s
s
e
v
er
al
c
h
allen
g
es
t
h
at
a
f
f
ec
t
its
p
r
o
d
u
c
tio
n
.
T
h
ese
ch
alle
n
g
es
ar
e
s
u
ch
as
li
m
i
tatio
n
s
in
th
e
e
n
v
ir
o
n
m
en
t
t
h
at
m
a
y
f
o
r
ce
r
o
b
o
ts
to
m
o
v
e
to
g
et
h
er
,
r
o
b
o
t in
ter
f
er
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ce
w
it
h
ea
ch
o
th
er
o
r
th
e
r
ed
u
n
d
an
c
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d
u
e
to
m
is
s
in
g
o
f
s
h
ar
ed
in
f
o
r
m
atio
n
[
1
5
]
.
Du
r
in
g
MR
S
ex
p
lo
r
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p
r
o
ce
s
s
,
it
is
n
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s
s
ar
y
f
o
r
ea
ch
r
o
b
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t
t
o
h
av
e
en
o
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g
h
in
f
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m
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tio
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ab
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t
th
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ex
p
lo
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ar
ea
s
o
f
th
e
e
n
v
ir
o
n
m
e
n
t,
s
o
t
h
e
r
o
b
o
ts
ca
n
p
lan
th
e
ir
p
ath
s
a
n
d
co
o
r
d
in
ate
th
eir
ac
tio
n
s
.
A
r
o
b
o
t
ca
n
in
d
i
v
id
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al
l
y
e
x
p
lo
r
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a
d
if
f
er
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t
ar
ea
s
o
f
th
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n
v
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m
e
n
t
,
b
u
t
w
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an
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co
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r
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in
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it
m
a
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e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
R
A
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N:
2089
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4856
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r
a
tio
n
S
tr
a
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T
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ab
s
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f
co
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ts
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e
x
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n
ec
ess
ar
y
to
i
m
p
r
o
v
e
t
h
e
ex
p
lo
r
atio
n
e
f
f
icien
c
y
[
1
5
]
,
[
1
6
]
.
T
h
e
co
o
r
d
in
atio
n
is
an
es
s
e
n
tial
tas
k
o
f
t
h
e
M
R
S
ex
p
lo
r
atio
n
an
d
s
o
t
h
e
s
y
s
te
m
p
e
r
f
o
r
m
an
ce
(
ex
ec
u
tio
n
ti
m
e
a
n
d
s
y
s
te
m
u
tili
t
y
)
is
a
f
f
ec
ted
b
y
its
q
u
alit
y
[
1
3
]
-
[
1
6
]
.
C
o
o
r
d
in
atio
n
in
MRS
e
x
p
lo
r
atio
n
i
s
u
s
ed
to
co
m
p
lete
t
h
e
o
v
er
al
l
tas
k
as
s
i
g
n
ed
to
th
e
MR
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t
ea
m
,
m
er
g
e
th
e
o
b
tain
ed
i
n
f
o
r
m
at
io
n
b
y
s
e
v
er
al
r
o
b
o
ts
,
d
ea
l
w
ith
li
m
i
ted
co
m
m
u
n
icat
io
n
,
ass
i
g
n
tas
k
s
to
in
d
iv
id
u
al
r
o
b
o
ts
,
s
p
ec
if
y
a
s
et
o
f
r
u
les,
in
ter
ac
t
to
ea
ch
i
n
d
iv
id
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al
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o
b
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,
an
d
o
v
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co
m
e
t
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i
n
ter
f
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en
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s
b
etw
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t
h
e
r
o
b
o
ts
s
u
ch
th
a
t
t
h
e
co
o
r
d
in
atio
n
ca
n
b
e
ac
h
iev
ed
m
o
r
e
e
f
f
icien
tl
y
at
g
l
o
b
al
lev
el
[
1
6
]
-
[
1
9
]
.
I
n
s
p
ite
o
f
a
lo
t
o
f
d
e
v
elo
p
m
e
n
t
h
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d
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i
n
M
R
S
ex
p
l
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ar
e
s
till
p
r
esen
t.
T
h
ese
is
s
u
e
s
in
cl
u
d
e
co
o
p
er
atio
n
co
n
tr
o
l,
co
n
cu
r
r
en
t
lo
ca
liz
atio
n
,
m
ap
p
i
n
g
,
co
lli
s
io
n
av
o
id
an
ce
,
tas
k
p
lan
n
i
n
g
,
co
m
m
u
n
icatio
n
a
m
o
n
g
r
o
b
o
ts
,
co
o
r
d
in
atio
n
,
n
a
v
ig
a
tio
n
an
d
ex
p
lo
r
atio
n
,
etc
.
A
s
an
ex
a
m
p
le,
Fig
u
r
e
1
s
h
o
w
s
th
at
th
r
ee
r
o
b
o
ts
tr
ies
to
ex
p
lo
r
e
th
e
e
n
v
ir
o
n
m
e
n
t
a
n
d
n
a
v
i
g
ate
to
th
e
ir
g
o
al
lo
ca
tio
n
s
.
W
h
ile
R
o
b
o
t
3
ca
n
n
av
i
g
ate
to
its
g
o
al,
ig
n
o
r
i
n
g
t
h
e
r
e
m
ai
n
i
n
g
r
o
b
o
ts
,
R
o
b
o
ts
1
an
d
2
n
ee
d
to
c
o
o
r
d
in
ate
s
o
as
n
o
t
to
cr
o
s
s
th
e
n
ar
r
o
w
d
o
o
r
w
a
y
s
i
m
u
lta
n
eo
u
s
l
y
[
2
0
]
.
Fig
u
r
e
1
.
An
ex
a
m
p
le
o
f
s
i
m
p
l
e
n
av
i
g
atio
n
tas
k
Mo
s
t
o
f
p
r
ev
io
u
s
s
tu
d
ie
s
in
th
is
p
o
in
t
f
o
cu
s
o
n
th
e
co
o
r
d
in
atio
n
b
et
w
ee
n
i
n
d
iv
id
u
al
r
o
b
o
ts
to
d
ec
r
ea
s
e
ex
p
lo
r
atio
n
ti
m
e,
b
u
t
o
n
l
y
f
e
w
p
ap
er
s
f
o
cu
s
o
n
h
o
w
co
llab
o
r
atio
n
s
b
et
w
ee
n
r
o
b
o
ts
af
f
ec
t
th
e
ex
p
lo
r
atio
n
tas
k
its
el
f
[
1
2
]
,
[
2
1
]
,
[
2
2
]
.
I
n
th
i
s
p
ap
er
th
e
c
o
o
r
d
in
atio
n
o
f
M
R
S
e
x
p
lo
r
atio
n
is
s
t
u
d
ied
an
d
a
s
et
o
f
co
m
m
o
n
r
ec
en
tl
y
u
s
ed
alg
o
r
ith
m
s
ar
e
p
r
esen
ted
an
d
co
m
p
ar
ed
f
o
r
a
s
et
o
f
d
if
f
er
e
n
t
tea
m
s
izes
a
n
d
d
if
f
er
en
t
en
v
i
r
o
n
m
e
n
t
s
tr
u
c
tu
r
es.
T
h
e
p
ap
er
is
o
r
g
an
ized
as
it
f
o
llo
w
s
.
A
r
e
v
ie
w
o
f
co
o
r
d
in
atio
n
i
n
MR
S
is
d
i
s
cu
s
s
ed
i
n
s
ec
tio
n
2
,
w
h
ile
th
e
p
r
o
b
lem
o
f
ex
p
lo
r
in
g
a
n
u
n
k
n
o
w
n
e
n
v
ir
o
n
m
e
n
t
i
s
d
escr
ib
ed
an
d
f
o
r
m
u
la
ted
in
s
ec
tio
n
3
.
T
h
e
m
u
lti
-
r
o
b
o
t
ex
p
lo
r
atio
n
alg
o
r
ith
m
s
ar
e
d
i
s
cu
s
s
ed
in
s
ec
tio
n
4
,
a
co
m
p
ar
is
o
n
b
et
w
ee
n
th
e
p
er
f
o
r
m
a
n
ce
o
f
co
o
r
d
in
atio
n
s
tr
ateg
ie
s
is
s
h
o
w
ed
an
d
an
al
y
ze
d
in
s
ec
tio
n
5
,
an
d
f
in
a
ll
y
o
u
r
w
o
r
k
is
co
n
clu
d
ed
w
it
h
s
u
g
g
es
tio
n
f
o
r
f
u
t
u
r
e
w
o
r
k
s
is
p
r
esen
ted
in
s
ec
t
io
n
6
.
2.
T
HE
M
RS C
O
O
RDINAT
I
O
N
T
ASK
S
T
ask
co
o
r
d
in
atio
n
in
M
R
S
h
as
b
ee
n
d
iv
id
ed
in
to
th
r
ee
ca
teg
o
r
ies
ac
co
r
d
in
g
to
th
e
ar
ch
itec
tu
r
e
o
f
th
e
r
o
b
o
ts
team
.
2
.
1
.
T
he
Dec
ent
ra
lized
Co
o
rdi
na
t
io
n Ar
chit
ec
t
ure
I
n
th
i
s
ar
ch
itect
u
r
e
th
er
e
is
n
o
ce
n
tr
al
co
n
tr
o
l
r
o
b
o
t
an
d
a
ll
th
e
r
o
b
o
ts
ar
e
eq
u
al
w
i
th
r
esp
ec
t
to
co
n
tr
o
l
an
d
ar
e
co
m
p
letel
y
au
to
n
o
m
o
u
s
i
n
t
h
e
d
ec
is
io
n
m
a
k
i
n
g
p
r
o
ce
s
s
.
I
t
is
also
ca
lled
d
is
tr
i
b
u
ted
ar
ch
itect
u
r
e
in
w
h
ich
ea
c
h
r
o
b
o
t
in
t
h
e
tea
m
is
r
esp
o
n
s
ib
l
e
f
o
r
cr
ea
ti
n
g
its
i
n
d
iv
id
u
al
m
ap
p
in
g
.
I
n
d
i
v
id
u
a
l
m
ap
p
in
g
i
n
f
o
r
m
atio
n
ar
e
ex
c
h
an
g
ed
b
et
w
ee
n
r
o
b
o
ts
w
h
en
t
h
e
y
m
ee
t
ea
ch
o
th
er
i
n
o
r
d
er
to
b
u
ild
a
co
m
p
lete
m
ap
m
o
d
el.
T
h
e
d
ec
en
tr
alize
d
co
o
r
d
in
at
io
n
r
esp
o
n
d
s
to
d
y
n
a
m
ic
e
n
v
ir
o
n
m
e
n
ts
in
a
s
u
b
o
p
ti
m
al
w
a
y
[
2
3
]
.
T
h
e
d
ec
en
tr
alize
d
co
o
r
d
in
atio
n
h
a
s
b
ee
n
i
m
p
le
m
en
ted
in
v
ar
io
u
s
ap
p
licatio
n
s
o
f
M
R
S
e
x
p
lo
r
atio
n
s
u
c
h
as
[
2
4
]
-
[
3
4
]
.
T
h
e
h
ier
ar
ch
y
o
f
d
ec
en
tr
alize
d
ap
p
r
o
ac
h
is
s
h
o
w
n
i
n
Fi
g
u
r
e
2
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4856
I
J
R
A
,
Vo
l.
7
,
No
.
1
,
Ma
r
ch
2
0
1
8
:
48
–
58
50
2
.
2
.
T
he
Cent
ra
lized
Co
o
rdi
na
t
io
n Ar
chit
ec
t
ure
I
n
ce
n
tr
alize
d
co
o
r
d
in
atio
n
ar
c
h
itect
u
r
e,
th
er
e
is
a
ce
n
tr
al
co
n
tr
o
l r
o
b
o
t (
lead
er
)
th
at
h
a
s
t
h
e
ab
ilit
y
to
co
m
m
u
n
icate
w
i
th
a
ll o
th
er
r
o
b
o
ts
,
in
o
r
d
er
to
s
h
ar
e
t
h
e
g
lo
b
al
in
f
o
r
m
atio
n
ab
o
u
t t
h
e
e
n
v
ir
o
n
m
e
n
t a
n
d
r
o
b
o
ts
.
So
it
is
r
e
s
p
o
n
s
ib
le
f
o
r
m
ap
p
in
g
b
y
co
llecti
n
g
d
ata
f
r
o
m
o
th
er
r
o
b
o
ts
.
T
h
is
ar
ch
itectu
r
e
p
er
f
o
r
m
s
w
ell
f
o
r
a
s
m
al
l
n
u
m
b
er
o
f
r
o
b
o
ts
an
d
r
u
n
f
a
s
ter
t
h
an
d
ec
e
n
tr
alize
d
c
o
o
r
d
in
atio
n
,
b
u
t
it
b
ec
o
m
e
s
i
n
ef
f
icie
n
t
f
o
r
lar
g
e
n
u
m
b
er
o
f
r
o
b
o
ts
d
u
e
to
th
e
in
f
o
r
m
atio
n
lo
s
s
e
s
a
n
d
h
i
g
h
er
co
m
m
u
n
icatio
n
o
v
er
h
ea
d
.
T
h
is
co
m
m
u
n
icat
io
n
o
v
er
h
ea
d
m
a
y
lead
to
co
m
m
u
n
icat
io
n
f
a
ilu
r
e
a
n
d
o
th
er
u
n
ce
r
tai
n
tie
s
.
T
h
e
ce
n
tr
alize
d
ar
ch
itectu
r
e
also
p
r
o
d
u
ce
s
a
h
ig
h
l
y
v
u
l
n
er
ab
le
s
y
s
te
m
i
f
t
h
e
ce
n
tr
al
co
n
tr
o
l
r
o
b
o
t
m
al
f
u
n
ctio
n
s
an
d
th
e
e
n
t
ir
e
team
i
s
d
i
s
ab
led
u
n
le
s
s
t
h
er
e
is
an
alter
n
ati
v
e
r
o
b
o
t
[
2
]
,
[
3
5
]
.
T
h
er
e
ar
e
a
lo
t
o
f
s
tu
d
ies
b
elo
n
g
i
n
g
to
th
e
ce
n
tr
alize
d
ar
ch
itect
u
r
e
in
MR
S
ex
p
lo
r
a
tio
n
s
u
c
h
as
[
3
6
]
-
[
4
0
]
.
T
h
e
h
ier
ar
ch
y
o
f
ce
n
tr
alize
d
ap
p
r
o
ac
h
is
s
h
o
w
n
i
n
Fig
u
r
e.
3
.
Fig
u
r
e
2
.
T
h
e
Dec
en
tr
alize
d
Ap
p
r
o
ac
h
Hier
ar
ch
y
Fig
u
r
e
3
.
T
h
e
C
en
tr
alize
d
A
p
p
r
o
ac
h
Hier
ar
ch
y
2
.
3
.
T
he
H
y
brid Co
o
rdina
t
io
n A
rc
hite
ct
ure
T
h
e
H
y
b
r
id
co
o
r
d
in
atio
n
i
s
an
i
n
ter
m
ed
iate
b
et
w
ee
n
th
e
ce
n
tr
alize
d
ar
c
h
itect
u
r
e
an
d
t
h
e
d
ec
en
tr
alize
d
ar
ch
itect
u
r
e
[
3
9
]
.
T
h
e
co
n
tr
o
l
p
r
o
ce
s
s
is
ac
h
iev
ed
u
s
i
n
g
o
n
e
o
r
m
o
r
e
l
o
ca
l
ce
n
tr
al
co
n
tr
o
l
r
o
b
o
ts
.
T
h
is
s
it
u
atio
n
lead
s
to
th
e
o
r
g
an
izatio
n
o
f
r
o
b
o
ts
i
n
to
clu
s
ter
s
w
h
er
e
ea
c
h
cl
u
s
ter
is
r
e
s
p
o
n
s
ib
le
f
o
r
p
er
f
o
r
m
in
g
s
u
b
-
tas
k
s
i
n
d
iv
id
u
all
y
i
n
a
ce
n
tr
alize
d
m
a
n
n
er
[
4
1
]
-
[
4
4
]
.
T
h
e
h
y
b
r
id
co
o
r
d
in
atio
n
p
r
o
v
id
es
m
o
r
e
r
o
b
u
s
t
s
o
lu
tio
n
s
a
n
d
ab
le
to
in
f
lu
e
n
ce
t
h
e
en
tire
tea
m
’
s
ac
tio
n
s
t
h
r
o
u
g
h
g
lo
b
al
g
o
als
a
n
d
p
lan
s
[
1
0
]
,
[
2
3
]
,
[
3
1
]
,
[
4
5
]
,
[
4
6
]
.
3.
T
HE
M
RS E
XP
L
O
RA
T
I
O
N
OF
U
NK
NO
WN
E
NVI
RN
M
E
NT
S
T
h
e
MRS
ca
n
b
e
u
s
ed
to
ex
p
l
o
r
e
all
th
e
r
eg
io
n
s
o
f
a
n
e
n
v
ir
o
n
m
e
n
t
to
g
a
th
er
i
n
f
o
r
m
atio
n
,
ac
q
u
ir
e
a
g
r
ap
h
ical
r
ep
r
esen
ta
tio
n
,
d
etec
t a
ll th
e
u
n
k
n
o
w
n
p
lace
an
d
f
i
n
all
y
b
u
ild
t
h
e
g
lo
b
al
en
v
ir
o
n
m
en
t
m
ap
[
4
7
]
.
T
h
e
g
lo
b
al
en
v
ir
o
n
m
e
n
t
m
ap
ca
n
b
e
b
u
ilt
b
y
co
llect
in
g
lo
ca
l
m
ap
s
o
f
t
h
e
ex
p
lo
r
ed
ar
ea
s
b
y
ea
c
h
r
o
b
o
t
in
t
h
e
MRS
.
T
h
e
M
R
S
e
x
p
lo
r
atio
n
i
s
en
d
ed
w
h
e
n
t
h
e
g
lo
b
al
en
v
ir
o
n
m
e
n
t
m
ap
i
s
p
r
ese
n
ted
.
T
h
e
en
v
ir
o
n
m
en
t
m
ap
ca
n
b
e
r
ep
r
esen
ted
a
s
g
r
ap
h
s
(
Vo
r
o
n
o
i
d
iag
r
a
m
,
Vi
s
ib
ilit
y
g
r
ap
h
)
,
ce
lls
(
o
cc
u
p
an
c
y
g
r
id
s
)
,
p
o
ly
g
o
n
s
o
r
tr
ee
s
(
g
r
ap
h
w
it
h
o
u
t c
y
c
les)
[
4
]
,
[
2
1
]
,
[
1
2
]
,
[
4
7
]
.
3
.
1
.
T
he
P
ro
ble
m
De
s
cr
iptio
n
T
h
e
MRS
e
x
p
lo
r
atio
n
p
r
o
b
lem
i
s
d
ef
in
ed
a
s
t
h
e
p
r
o
b
le
m
o
f
ex
p
lo
r
in
g
a
n
e
n
v
ir
o
n
m
e
n
t
o
cc
u
p
ied
b
y
a
s
et
o
f
o
b
s
tacle
s
,
u
s
i
n
g
a
s
et
o
f
id
en
tical
m
o
b
ile
r
o
b
o
ts
.
T
h
e
f
o
u
r
m
ai
n
co
m
p
o
n
e
n
ts
t
h
at
a
f
f
e
ct
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
i
s
p
r
o
ce
s
s
ar
e
th
e
en
v
ir
o
n
m
en
t,
o
b
s
tacle
s
,
s
et
o
f
r
o
b
o
ts
an
d
th
e
ex
p
lo
r
atio
n
al
g
o
r
ith
m
.
3
.
1
.
1
.
E
nv
iro
n
m
e
nt
An
en
v
ir
o
n
m
e
n
t
is
co
n
s
id
er
ed
as
a
f
in
ite
t
w
o
-
d
i
m
e
n
s
io
n
al
s
p
ac
e
w
it
h
en
v
ir
o
n
m
e
n
tal
b
o
u
n
d
ar
y
a
n
d
it
ca
n
b
e
r
ep
r
esen
ted
as
ce
ll
b
ased
m
ap
o
r
g
r
ap
h
b
ased
m
ap
.
I
n
th
e
C
e
ll
-
B
ased
m
ap
,
th
e
en
v
ir
o
n
m
e
n
t
to
b
e
ex
p
lo
r
ed
ca
n
b
e
d
iv
id
ed
in
to
s
i
m
ilar
ce
ll
s
.
Du
r
i
n
g
t
h
e
e
x
p
lo
r
atio
n
p
r
o
ce
s
s
,
ea
ch
ce
ll
h
a
s
a
s
p
ec
if
ic
s
tate
f
r
o
m
f
o
u
r
s
tate
s
[
4
]
:
u
n
e
x
p
lo
r
ed
,
f
r
ee
,
w
all,
an
d
f
r
o
n
tier
.
T
h
e
u
n
e
x
p
lo
r
ed
ce
ll
h
as
n
o
t
b
ee
n
v
is
i
te
d
b
y
an
y
r
o
b
o
t,
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
R
A
I
SS
N:
2089
-
4856
E
xp
lo
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a
tio
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l sh
en
a
w
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51
f
r
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p
en
an
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is
ited
b
y
at
lea
s
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o
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w
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o
b
s
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ed
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eg
io
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I
n
th
e
Gr
ap
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ased
m
ap
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th
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e
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o
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m
e
n
t i
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n
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id
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ed
as a
g
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ap
h
co
n
s
i
s
ti
n
g
o
f
ed
g
e
s
a
n
d
v
er
tices.
T
h
is
g
r
ap
h
is
u
n
k
n
o
w
n
ap
r
io
r
i
w
h
er
e
n
o
ed
g
es a
n
d
n
o
v
er
tices a
r
e
k
n
o
w
n
[
7
]
,
[
2
2
]
.
3
.
1
.
2
.
O
bs
t
a
cles
T
h
e
en
v
ir
o
n
m
e
n
t
to
b
e
e
x
p
l
o
r
ed
is
o
cc
u
p
ied
b
y
a
s
et
o
f
r
an
d
o
m
l
y
,
s
tatio
n
ar
y
a
n
d
d
is
tr
ib
u
ted
o
b
s
tacle
s
w
ith
s
h
ap
e
s
an
d
p
o
s
itio
n
s
w
h
ic
h
ar
e
eith
er
k
n
o
w
n
o
r
u
n
k
n
o
w
n
[
3
6
]
.
3
.
1
.
3
.
M
o
bil
e
Ro
bo
t
s
A
tea
m
o
f
m
o
b
ile
r
o
b
o
ts
p
e
r
f
o
r
m
s
t
h
e
ex
p
lo
r
atio
n
tas
k
.
T
h
ese
team
r
o
b
o
ts
m
a
y
b
e
in
a
s
i
m
ila
r
s
tr
u
ct
u
r
e
(
Ho
m
o
g
e
n
eo
u
s
r
o
b
o
ts
)
o
r
in
a
d
if
f
er
en
t
s
tr
u
ct
u
r
e
(
h
eter
o
g
o
n
o
u
s
r
o
b
o
ts
)
.
T
h
ese
r
o
b
o
ts
ca
n
f
r
ee
l
y
m
o
v
e
f
r
o
m
o
n
e
ce
ll
to
an
y
o
n
e
o
f
its
n
ei
g
h
b
o
r
s
d
ep
en
d
i
n
g
o
n
s
o
m
e
lo
ca
l
in
f
o
r
m
a
tio
n
ab
o
u
t
th
e
n
ei
g
h
b
o
r
r
o
b
o
ts
o
r
th
e
n
ei
g
h
b
o
r
ce
lls
[
1
]
,
[
2
1
]
.
3
.
1
.
4
.
E
x
plo
ra
t
io
n
Alg
o
rit
h
m
s
A
t
ev
er
y
ti
m
e
s
tep
,
t
h
e
e
x
p
lo
r
atio
n
al
g
o
r
ith
m
c
h
o
o
s
es
o
n
e
o
f
t
h
e
f
r
o
n
tier
ce
lls
to
b
e
t
h
e
n
ex
t
tar
g
et
f
o
r
a
r
o
b
o
t
b
ased
o
n
its
d
is
tan
ce
an
d
t
h
e
s
ize
o
f
t
h
e
e
n
v
ir
o
n
m
e
n
t
to
b
e
ex
p
lo
r
ed
at
th
e
cu
r
r
en
t
s
tep
.
E
x
p
lo
r
atio
n
al
g
o
r
ith
m
s
a
ls
o
u
p
d
ate
th
e
ex
is
ti
n
g
m
ap
b
y
t
h
e
n
e
w
i
n
f
o
r
m
atio
n
a
n
d
ass
ig
n
a
p
ar
ticu
lar
g
o
al
to
r
o
b
o
ts
u
s
in
g
a
d
ef
in
ed
co
s
t
f
u
n
ct
io
n
.
T
h
e
s
h
o
r
test
p
ath
f
r
o
m
th
e
r
o
b
o
ts
to
th
e
g
o
als
a
r
e
th
en
f
o
u
n
d
[
5
]
.
Fin
all
y
,
th
e
r
o
b
o
ts
ar
e
n
a
v
i
g
at
ed
alo
n
g
t
h
e
p
at
h
s
.
A
s
e
t
o
f
c
o
m
m
o
n
e
x
p
lo
r
atio
n
al
g
o
r
ith
m
s
w
il
l
b
e
d
is
c
u
s
s
ed
in
d
etail
in
s
ec
tio
n
4
.
3
.
2
.
T
he
P
ro
ble
m
F
o
r
m
ula
t
i
o
n
T
h
e
MRS
ex
p
lo
r
atio
n
p
r
o
b
le
m
is
co
n
s
id
er
ed
as
a
r
ep
etitiv
e
tas
k
ass
ig
n
m
en
ts
.
A
t
ea
c
h
s
tep
,
a
r
o
b
o
t
is
as
s
ig
n
ed
to
a
g
o
al
w
it
h
m
i
n
i
m
u
m
ex
p
lo
r
atio
n
ti
m
e.
T
h
e
r
o
b
o
t
m
u
s
t
tr
av
el
d
is
tan
ce
to
r
ea
ch
th
e
g
o
al
.
T
h
e
ex
p
lo
r
atio
n
ti
m
e
is
ap
p
r
o
x
im
a
ted
b
y
[
4
8
]
.
T
h
e
f
o
llo
w
i
n
g
f
o
r
m
u
la
f
o
r
tr
av
eli
n
g
B
er
li
n
r
ea
ch
es
t
h
e
d
esti
n
atio
n
as
s
h
o
w
n
i
n
eq
u
atio
n
(
1
)
.
(
1
)
T
h
e
o
b
j
ec
tiv
e
is
to
f
i
n
d
a
s
eq
u
en
ce
o
f
tr
aj
ec
to
r
ies
(
|
)
a
m
o
n
g
all
p
o
s
s
ib
le
tr
aj
ec
to
r
ies
|
)
th
at
h
a
v
e
a
m
i
n
i
m
u
m
ex
p
ec
ted
m
ea
n
ti
m
e
o
f
th
e
ex
p
lo
r
atio
n
en
v
ir
o
n
m
e
n
t
as
s
h
o
w
n
i
n
eq
u
atio
n
(
2
)
.
W
h
er
e
an
d
ar
e
tr
a
j
ec
to
r
ies
o
f
th
e
r
o
b
o
t,
T
tim
e
n
ee
d
ed
t
o
tr
av
er
s
e
R
a
n
d
th
e
f
o
r
m
u
la
as
s
h
o
w
n
in
eq
u
a
tio
n
(
3
)
.
|
)
(
2
)
|
)
∑
)
(
3
)
W
h
er
e
)
is
th
e
p
r
o
b
a
b
ilit
y
d
en
s
it
y
f
u
n
ctio
n
w
h
e
n
a
p
r
io
r
in
f
o
r
m
atio
n
ab
o
u
t
o
b
j
ec
ts
is
av
ail
ab
le.
T
h
e
)
is
co
n
s
id
er
ed
to
b
e
th
e
r
atio
o
f
th
e
ar
ea
n
e
w
l
y
m
ea
s
u
r
ed
at
ti
m
e
t
w
h
en
t
h
e
r
o
b
o
ts
f
o
llo
w
th
e
tr
aj
ec
to
r
ies
an
d
th
e
ar
ea
o
f
t
h
e
w
h
o
le
e
n
v
i
r
o
n
m
e
n
t
th
e
r
o
b
o
ts
o
p
er
ate
,
w
h
e
n
th
e
p
r
io
r
in
f
o
r
m
atio
n
is
n
o
t
av
ailab
le.
T
h
e
f
o
llo
w
i
n
g
f
o
r
m
u
la
f
o
r
p
r
o
b
ab
ilit
y
d
en
s
i
t
y
as
s
h
o
w
n
i
n
eq
u
atio
n
(
4
)
.
)
(
4
)
T
h
er
ef
o
r
e
E
q
u
atio
n
2
ca
n
b
e
r
e
w
r
itte
n
as
s
h
o
w
i
n
eq
u
atio
n
(
5
)
.
|
)
∑
(
5
)
Ass
u
m
ptio
n
s
:
i.
E
ac
h
r
o
b
o
t
in
itiall
y
h
as
n
o
in
f
o
r
m
atio
n
ab
o
u
t
o
th
er
r
o
b
o
ts
an
d
th
e
en
v
ir
o
n
m
en
t
e
x
ce
p
t
th
e
r
elativ
e
d
is
tan
ce
s
w
ith
o
t
h
er
r
o
b
o
ts
.
ii.
A
ll r
o
b
o
ts
h
a
v
e
th
e
s
a
m
e
g
eo
m
etr
ical
s
ize
s
eq
u
al
to
s
ize
o
f
a
g
r
id
ce
ll.
iii.
E
ac
h
r
o
b
o
t is ab
le
to
co
m
m
u
n
i
ca
te
w
it
h
t
h
e
en
v
ir
o
n
m
e
n
t
w
it
h
n
o
d
ela
y
.
iv
.
A
ll r
o
b
o
ts
ca
n
m
o
v
e
u
p
w
ar
d
,
d
o
w
n
w
ar
d
,
lef
t
w
ar
d
,
an
d
r
ig
h
t
w
ar
d
o
n
l
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4856
I
J
R
A
,
Vo
l.
7
,
No
.
1
,
Ma
r
ch
2
0
1
8
:
48
–
58
52
4.
M
UL
T
I
-
RO
B
O
T
E
XP
L
O
R
AT
I
O
N
A
L
G
O
RI
T
H
M
S
Ma
n
y
e
x
p
lo
r
atio
n
s
tr
ateg
ie
s
ex
is
t,
f
o
u
r
m
et
h
o
d
s
ar
e
s
t
u
d
ied
w
ith
in
t
h
e
p
r
ese
n
ted
ex
p
lo
r
atio
n
f
r
a
m
e
w
o
r
k
,
an
d
th
e
f
o
llo
w
in
g
p
ar
ag
r
ap
h
g
iv
e
s
an
o
v
er
v
ie
w
o
f
th
e
s
e
s
tr
ate
g
ies.
4
.
1
.
T
he
F
ro
ntie
r
B
a
s
ed
E
x
plo
ra
t
io
n Alg
o
rit
h
m
T
h
e
k
e
y
id
ea
b
eh
in
d
a
f
r
o
n
ti
er
b
ased
ex
p
lo
r
atio
n
alg
o
r
ith
m
is
to
g
ai
n
n
e
w
i
n
f
o
r
m
atio
n
ab
o
u
t
a
n
en
v
ir
o
n
m
e
n
t
a
n
d
n
a
v
i
g
ate
to
th
e
b
o
u
n
d
ar
y
b
et
w
ee
n
e
x
p
l
o
r
ed
an
d
u
n
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Fig
u
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4
.
T
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Fro
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ased
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Fig
u
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5
.
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h
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R
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ased
ex
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alg
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4
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2
.
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Ro
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m
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ased
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tatic
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ir
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m
en
ts
[
1
7
]
,
[
2
7
]
,
[
5
0
]
.
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5
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4
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Fig
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5.
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RE
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A
.
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a
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R.
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i
w
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ri
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d
A
.
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h
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k
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u
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Ch
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A
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in
h
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A
De
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tralize
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to
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f
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tru
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In
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In
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0
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h
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a
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n
d
ia.
[3
]
K.
Ce
sa
re
,
R.
S
k
e
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le,
S
.
Yo
o
,
Y.
Zh
a
n
g
a
n
d
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.
Ho
ll
in
g
e
r,
“
M
u
lt
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-
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Ex
p
lo
ra
ti
o
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w
it
h
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im
it
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m
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ica
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a
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d
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ry
,
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In
tern
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Co
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o
n
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b
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t
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a
n
d
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u
to
m
a
ti
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n
(ICRA
),
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6
-
3
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M
a
y
2
0
1
5
,
S
e
a
tt
le,
WA
,
USA
.
[4
]
Y.
W
a
n
g
,
A
.
L
i
a
n
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a
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d
H.
G
u
a
n
,
“
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ro
n
ti
e
r
-
b
a
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M
u
lt
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-
R
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b
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Ex
p
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in
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P
a
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c
le
S
w
a
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m
Op
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m
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ti
o
n
,
”
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E
S
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m
p
o
siu
m
o
n
S
w
a
r
m
In
telli
g
e
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(S
IS
),
1
1
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1
5
A
p
r
2
0
1
1
,
P
a
r
is,
F
ra
n
c
e
.
[5
]
M
.
Ra
jes
h
,
G
.
R.
Ja
se
a
n
d
T
.
S
.
B.
S
u
d
a
rsh
a
n
,
”
M
u
lt
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b
o
t
Ex
p
l
o
ra
ti
o
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a
n
d
M
a
p
p
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u
si
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F
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r
Ce
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Co
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c
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p
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”
A
n
n
u
a
l
IEE
E
I
n
d
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f
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re
n
c
e
(IND
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),
1
1
-
1
3
De
c
2
0
1
4
,
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n
e
,
In
d
ia.
[6
]
T
.
G
u
n
n
a
n
d
J.
A
n
d
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rso
n
,
“
Eff
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c
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T
a
sk
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ll
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f
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Ev
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a
m
s
in
Da
n
g
e
ro
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s
En
v
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m
e
n
ts,
”
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W
IC/A
C
M
In
ter
n
a
ti
o
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Co
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n
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lo
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y
(I
AT
),
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l
1
1
4
,
1
7
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2
0
No
v
2
0
1
3
,
A
tl
a
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ta,
G
A
,
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A
.
[7
]
S
.
C.
Na
g
a
v
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,
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.
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a
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h
h
a
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a
n
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A
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in
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a
,
“
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u
lt
i
-
R
o
b
o
t
G
ra
p
h
Ex
p
lo
ra
ti
o
n
a
n
d
M
a
p
Bu
il
d
in
g
w
it
h
Co
ll
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n
Av
o
id
a
n
c
e
:
A
De
c
e
n
tralize
d
A
p
p
ro
a
c
h
,
”
S
p
r
in
g
e
r,
S
c
ien
c
e
+
Bu
sin
e
ss
M
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d
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rd
re
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h
t
,
1
1
N
o
v
2
0
1
5
.
[8
]
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.
A
n
d
ries
a
n
d
F
.
Ch
a
rp
il
let,
“
M
u
lt
i
-
r
o
b
o
t
e
x
p
lo
ra
ti
o
n
o
f
u
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v
iro
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m
e
n
ts
w
it
h
id
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n
ti
f
ica
ti
o
n
o
f
e
x
p
lo
ra
ti
o
n
c
o
m
p
letio
n
a
n
d
p
o
st
-
e
x
p
l
o
ra
ti
o
n
re
n
d
e
z
v
o
u
s
u
si
n
g
a
n
t
a
lg
o
rit
h
m
s,”
IEE
E/
RS
J
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
In
telli
g
e
n
t
Ro
b
o
ts
a
n
d
S
y
ste
m
s (I
ROS),
3
-
7
No
v
2
0
1
3
.
T
o
k
y
o
,
Ja
p
a
n
.
[9
]
B.
W
a
n
g
a
n
d
S
.
Qi
n
,
“
M
u
lt
i
-
r
o
b
o
t
E
n
v
iro
n
m
e
n
t
Ex
p
l
o
ra
ti
o
n
Ba
s
e
d
o
n
L
a
b
e
l
M
a
p
s
Bu
il
d
in
g
v
ia
Re
c
o
g
n
it
io
n
o
f
F
ro
n
t
iers
,
”
IEE
E
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
M
u
lt
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n
s
o
r
F
u
s
io
n
a
n
d
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f
o
rm
a
ti
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n
In
teg
ra
ti
o
n
f
o
r
In
telli
g
e
n
t
S
y
st
e
m
s (M
F
I),
28
-
2
9
S
e
p
2
0
1
4
,
Be
ij
in
g
,
Ch
i
n
a
.
[1
0
]
S
.
G
ra
y
so
n
,
“
S
e
a
rc
h
&
Re
s
c
u
e
u
sin
g
M
u
lt
i
-
R
o
b
o
t
S
y
ste
m
s,”
S
c
h
o
o
l
o
f
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
In
f
o
rm
a
ti
c
s,
Un
iv
e
rsit
y
Co
ll
e
g
e
Du
b
li
n
,
2
0
1
4
.
[1
1
]
M
.
A
l
-
k
h
a
w
a
ld
a
h
,
T
.
M
.
Yo
u
n
e
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.
Nisira
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lsh
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sin
,
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A
u
to
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M
u
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Ro
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e
a
rc
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tatio
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T
a
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In
tern
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Jo
u
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rin
g
,
Vo
l
4
(1
),
2
0
1
4
,
p
p
.
9
-
15.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
R
A
I
SS
N:
2089
-
4856
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lo
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tr
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(
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57
[1
2
]
R.
Re
id
,
A
.
Ca
n
n
,
C.
M
e
ik
lejo
h
n
,
L
.
P
o
li
,
A
.
Bo
e
in
g
a
n
d
T
.
Bra
u
n
l,
”
Co
o
p
e
ra
ti
v
e
M
u
lt
i
-
Ro
b
o
t
Na
v
ig
a
ti
o
n
,
Ex
p
lo
ra
ti
o
n
,
M
a
p
p
i
n
g
a
n
d
Ob
jec
t
De
tec
ti
o
n
w
it
h
ROS,
”
IEE
E
In
telli
g
e
n
t
V
e
h
icle
s
S
y
m
p
o
siu
m
(I
V
),
2
3
-
2
6
Ju
n
2
0
1
3
,
G
o
ld
Co
a
st,
A
u
stra
li
a
.
[1
3
]
A
.
F
a
rin
e
ll
ia,
N.
Bo
sc
o
l
o
c
,
E.
Za
n
o
tt
o
b
a
n
d
E.
P
a
g
e
ll
o
b
,
“
A
d
v
a
n
c
e
d
A
p
p
ro
a
c
h
e
s
f
o
r
M
u
lt
i
-
Ro
b
o
t
C
o
o
rd
in
a
ti
o
n
in
L
o
g
isti
c
S
c
e
n
a
rio
s,” El
se
v
ier,
Ro
b
o
ti
c
s an
d
A
u
to
n
o
m
o
u
s S
y
ste
m
s,
V
o
l
9
0
,
A
p
r
2
0
1
7
,
p
p
3
4
-
4
4
.
[1
4
]
N.
P
a
lm
ieri1
,
X
.
S
.
Ya
n
g
,
S
.
M
a
r
a
n
o
,
“
Co
o
rd
i
n
a
ti
o
n
T
e
c
h
n
iq
u
e
s o
f
M
o
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il
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Ro
b
o
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w
it
h
E
n
e
rg
y
Co
n
stra
in
ts,
”
IEE
E
In
tern
a
ti
o
n
a
l
S
y
m
p
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siu
m
o
n
P
e
rf
o
r
m
a
n
c
e
Ev
a
lu
a
ti
o
n
o
f
Co
m
p
u
t
e
r
a
n
d
T
e
l
e
c
o
m
m
u
n
ica
ti
o
n
S
y
ste
m
s
(S
P
ECT
S
),
24
-
2
7
J
u
l
2
0
1
6
,
M
o
n
trea
l,
QC,
C
a
n
a
d
a
.
[1
5
]
L
.
W
u
,
D.
P
u
ig
a
n
d
M
.
A
.
G
a
rc
i
a
,
“
Ba
lan
c
e
d
M
u
lt
i
-
R
o
b
o
t
Ex
p
lo
r
a
ti
o
n
t
h
ro
u
g
h
a
G
lo
b
a
l
Op
ti
m
iza
ti
o
n
S
trate
g
y
,
”
Jo
u
rn
a
l
o
f
P
h
y
sic
a
l
A
g
e
n
ts,
Vo
l.
4
,
n
o
1
,
Ja
n
2
0
1
0
.
[1
6
]
R.
G
.
Co
lare
s
a
n
d
L
.
C
h
a
im
o
w
i
c
z
,
“
A
No
v
e
l
Dista
n
c
e
Co
st
A
p
p
ro
a
c
h
f
o
r
M
u
lt
i
-
ro
b
o
t
In
teg
ra
ted
Ex
p
l
o
ra
ti
o
n
,
”
IEE
E
1
2
t
h
L
a
ti
n
A
m
e
ri
c
a
n
Ro
b
o
ti
c
s
S
y
m
p
o
siu
m
a
n
d
3
rd
Bra
z
il
ian
S
y
m
p
o
siu
m
o
n
R
o
b
o
ti
c
s,
2
9
-
3
1
Oc
t
2
0
1
5
,
Ub
e
rlan
d
ia,
Bra
z
il
.
[1
7
]
J.
d
.
H
o
o
g
,
S
.
Ca
m
e
ro
n
a
n
d
A
.
Vi
ss
e
r,
“
Ro
le
-
Ba
se
d
A
u
to
n
o
m
o
u
s
M
u
lt
i
-
R
o
b
o
t
Ex
p
lo
ra
ti
o
n
,
”
0
9
.
IE
EE
In
ter
n
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
F
u
tu
re
Co
m
p
u
ti
n
g
,
S
e
rv
ice
Co
m
p
u
tatio
n
,
C
o
g
n
it
iv
e
,
A
d
a
p
ti
v
e
,
Co
n
te
n
t,
P
a
tt
e
rn
s
,
1
5
-
2
0
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o
v
2
0
0
9
,
p
p
4
8
2
-
4
8
7
,
A
t
h
e
n
s,
G
re
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e
.
[1
8
]
D.
F
o
x
,
J.
Ko
,
K.
Ko
n
o
li
g
e
,
B,
L
i
m
k
e
tk
a
i,
D.
S
c
h
u
lz
a
n
d
B.
S
tew
a
rt,
“
Distrib
u
ted
M
u
lt
i
-
r
o
b
o
t
E
x
p
lo
ra
ti
o
n
a
n
d
M
a
p
p
i
n
g
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Ro
b
o
ti
c
s an
d
A
u
to
m
a
ti
o
n
,
V
o
l
9
4
,
Ju
l
2
0
0
6
,
p
p
1
3
2
5
-
1
3
3
9
.
[1
9
]
W
.
Bu
rg
a
rd
,
M
.
M
o
o
rs,
C.
S
tac
h
n
iss
a
n
d
F
.
E.
S
c
h
n
e
id
e
r,
“
Co
o
rd
i
n
a
ted
M
u
l
ti
-
Ro
b
o
t
Ex
p
l
o
ra
ti
o
n
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s o
n
R
o
b
o
ti
c
s,
V
o
l.
2
1
,
Ju
n
e
2
0
0
5
,
n
o
3
,
p
p
3
7
6
-
3
8
6
.
[2
0
]
F
.
S
.
M
e
lo
,
M
.
V
e
l
o
so
,
“
De
c
e
n
tr
a
li
z
e
d
M
DP
s
w
it
h
sp
a
rse
in
tera
c
ti
o
n
s,”
El
se
v
ier,
B.
V
,
A
rti
f
icia
l
In
telli
g
e
n
c
e
,
V
o
l
1
7
5
,
2
0
1
1
,
p
p
.
1
7
5
7
–
1
7
8
9
.
[2
1
]
A
.
P
a
l.
R.
T
iw
a
ri
a
n
d
A
.
S
h
u
k
la,
“
M
u
lt
i
-
Ro
b
o
t
Ex
p
l
o
ra
ti
o
n
i
n
W
irele
ss
En
v
iro
n
m
e
n
ts,
”
S
p
rin
g
e
r,
S
c
ien
c
e
+
Bu
sin
e
ss
M
e
d
ia i
n
A
u
to
n
o
m
o
u
s Ro
b
o
ts
,
2
6
A
p
r
2
0
1
2
,
L
L
C.
[2
2
]
T
.
A
n
d
re
a
n
d
C
.
Be
tt
ste
tt
e
r,
“
C
o
ll
a
b
o
ra
ti
o
n
i
n
M
u
lt
i
-
R
o
b
o
t
Ex
p
lo
ra
ti
o
n
:
T
o
M
e
e
t
o
r
n
o
t
t
o
M
e
e
t?,”
S
p
rin
g
e
r,
Jo
u
rn
a
l
o
f
In
telli
g
e
n
t
&
R
o
b
o
ti
c
S
y
ste
m
s
,
V
o
l
8
2
,
M
a
y
2
0
1
6
,
p
p
3
2
5
–
3
3
7
.
[2
3
]
B.
Du
g
a
rjav
a
n
d
S
.
L
e
e
,
“
S
c
a
n
M
a
tch
i
n
g
Ba
se
d
M
u
lt
i
-
r
o
b
o
t
M
a
p
B
u
il
d
in
g
,
”
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
M
e
c
h
a
n
ica
l
a
n
d
I
n
d
u
strial
E
n
g
in
e
e
rin
g
(ICM
A
IE’
2
0
1
5
),
8
-
9
F
e
b
2
0
1
5
,
Ku
a
la L
u
m
p
u
r,
M
a
lay
sia
.
[2
4
]
X
.
Da
i
1
,
L
.
Jia
n
g
a
n
d
Y.
Z
h
a
o
,
“
Co
o
p
e
ra
ti
v
e
e
x
p
lo
ra
ti
o
n
b
a
se
d
o
n
s
u
p
e
rv
iso
ry
c
o
n
tro
l
o
f
m
u
lt
i
-
ro
b
o
t
sy
ste
m
s”
S
p
rin
g
e
r,
S
c
ie
n
c
e
+
Bu
sin
e
ss
M
e
d
i
a
in
A
u
to
n
o
m
o
u
s Ro
b
o
ts
,
1
4
Ja
n
2
0
1
6
,
Ne
w
Yo
rk
.
[2
5
]
C.
Ch
a
n
g
a
n
d
C.
T
sa
i,
“
Co
o
p
e
ra
ti
v
e
Ex
p
lo
r
a
ti
o
n
o
f
Ne
t
w
o
rk
e
d
M
u
lt
i
-
Ro
b
o
t
S
y
ste
m
s
U
sin
g
M
in
ima
l
In
f
o
rm
a
ti
o
n
En
tro
p
y
,
”
IEE
E
1
2
th
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
Ne
tw
o
rk
in
g
,
S
e
n
sin
g
a
n
d
Co
n
tro
l
Ho
w
a
rd
Civ
il
S
e
rv
ice
In
tern
a
ti
o
n
a
l
Ho
u
se
,
9
-
1
1
A
p
r
2
0
1
5
,
T
a
ip
e
i,
T
a
iw
a
n
.
[2
6
]
J.
Re
n
o
u
x
,
A
.
M
o
u
a
d
d
i
b
a
n
d
S
.
L
e
.
G
lo
a
n
n
e
c
,
“
A
d
e
c
i
sio
n
-
th
e
o
re
ti
c
p
lan
n
in
g
a
p
p
r
o
a
c
h
f
o
r
m
u
lt
i
-
ro
b
o
t
e
x
p
lo
ra
ti
o
n
a
n
d
e
v
e
n
t
se
a
rc
h
,
”
IEE
E/
RS
J
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
In
telli
g
e
n
t
Ro
b
o
ts
a
n
d
S
y
ste
m
s
(IROS),
Co
n
g
re
ss
Ce
n
ter
Ha
m
b
u
rg
,
S
e
p
t
2
8
-
Oc
t
2
2
0
1
5
.
Ha
m
b
u
rg
,
G
e
r
m
a
n
y
.
[2
7
]
V
.
S
p
iri
n
a
n
d
S
.
Ca
m
e
ro
n
,
“
Re
n
d
e
z
v
o
u
s
T
h
ro
u
g
h
Ob
sta
c
les
in
M
u
lt
i
-
A
g
e
n
t
Ex
p
lo
ra
ti
o
n
,
”
IE
E
E
In
tern
a
ti
o
n
a
l
S
y
m
p
o
siu
m
o
n
S
a
f
e
t
y
,
S
e
c
u
rit
y
,
a
n
d
Re
sc
u
e
Ro
b
o
ti
c
s (S
S
RR),
27
-
3
0
Oc
t
2
0
1
4
,
H
o
k
k
a
id
o
,
Ja
p
a
n.
[2
8
]
L
.
M
a
ti
g
n
o
n
,
L
.
Je
a
n
p
ierre
a
n
d
A
.
M
o
u
a
d
d
i
b
,
“
Distrib
u
ted
V
a
lu
e
F
u
n
c
ti
o
n
s
f
o
r
M
u
lt
i
-
Ro
b
o
t
Ex
p
lo
ra
ti
o
n
,
”
IEE
E
In
tern
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
Ro
b
o
ti
c
s an
d
A
u
to
m
a
ti
o
n
(ICRA
)
, 1
4
-
1
8
M
a
y
2
0
1
2
,
S
a
in
t
P
a
u
l,
M
N,
U
S
A
.
[2
9
]
L
.
M
a
ti
g
n
o
n
,
L
.
Je
a
n
p
ierre
a
n
d
A
.
M
o
u
a
d
d
i
b
,
“
Co
o
rd
in
a
ted
M
u
lt
i
-
R
o
b
o
t
Ex
p
lo
ra
ti
o
n
Un
d
e
r
Co
m
m
u
n
ica
ti
o
n
Co
n
stra
in
ts
Us
in
g
De
c
e
n
tralize
d
M
a
rk
o
v
D
e
c
isio
n
P
r
o
c
e
ss
e
s,”
Tw
e
n
t
y
-
S
ix
th
AA
A
I
Co
n
f
e
re
n
c
e
o
n
A
rti
f
icia
l
In
telli
g
e
n
c
e
,
2
0
1
2
.
[3
0
]
Z.
Ya
n
,
N.
Jo
u
a
n
d
e
a
u
a
n
d
A
.
A
.
Ch
e
rif
,
”
M
u
lt
i
-
ro
b
o
t
De
c
e
n
tralize
d
Ex
p
lo
ra
ti
o
n
Us
in
g
a
T
ra
d
e
-
b
a
se
d
A
p
p
ro
a
c
h
,
”
8
th
I
n
tern
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
I
n
f
o
rm
a
ti
c
s in
Co
n
tro
l,
A
u
to
m
a
ti
o
n
a
n
d
Ro
b
o
ti
c
s (ICINCO),
2
0
1
1
.
[3
1
]
A
.
D.
Ha
u
m
a
n
n
,
K.
D.
L
ist
m
a
n
n
a
n
d
V.
W
il
lert,
“
DisCo
v
e
ra
g
e
:
A
n
e
w
P
a
ra
d
ig
m
f
o
r
M
u
lt
i
-
Ro
b
o
t
Ex
p
lo
ra
ti
o
n
”
IEE
E
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
Ro
b
o
ti
c
s an
d
A
u
to
m
a
ti
o
n
(ICRA),
3
-
7
M
a
y
2
0
1
0
,
A
n
c
h
o
ra
g
e
,
A
K,
USA
.
[3
2
]
A
.
M
a
rjo
v
i,
J.
G
.
Nu
n
e
s,
L
.
M
a
rq
u
e
s
a
n
d
A
.
d
e
A
lme
id
a
,
“
M
u
lt
i
-
R
o
b
o
t
Ex
p
l
o
ra
ti
o
n
a
n
d
F
ire S
e
a
rc
h
in
g
,
”
IEE
E/
RS
J
In
tern
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
In
tell
ig
e
n
t
Ro
b
o
ts
a
n
d
S
y
ste
m
s,
1
1
-
1
5
Oc
t
2
0
0
9
,
S
t.
L
o
u
is,
USA
.
[3
3
]
L
.
W
u
,
M
.
A
.
G
a
rc
ia,
D.
P
u
ig
a
n
d
A
.
t
S
o
le,
“
V
o
r
o
n
o
i
-
Ba
se
d
S
p
a
c
e
P
a
rti
ti
o
n
in
g
f
o
r
Co
o
r
d
i
n
a
ted
M
u
lt
i
-
Ro
b
o
t
Ex
p
lo
ra
ti
o
n
,
”
Jo
u
rn
a
l
o
f
P
h
y
sic
a
l
Ag
e
n
ts,
V
o
l
.
1
,
n
o
.
1
,
S
e
p
2
0
0
7
.
[3
4
]
S
.
Om
id
sh
a
f
iei,
A
.
A
.
M
o
h
a
m
m
a
d
i,
C.
A
m
a
to
,
S
.
Y
L
iu
,
J.
P
.
Ho
w
a
n
d
J.
V
ian
,
“
De
c
e
n
tralize
d
c
o
n
tro
l
o
f
m
u
lt
i
-
ro
b
o
t
p
a
rti
a
ll
y
o
b
se
rv
a
b
le M
a
r
k
o
v
d
e
c
isio
n
p
r
o
c
e
ss
e
s u
sin
g
b
e
li
e
f
sp
a
c
e
m
a
c
ro
-
a
c
ti
o
n
s,” IE
EE
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
Ro
b
o
t
ics
Re
se
a
rc
h
,
V
o
l
.
3
6
(2
)
,
2
0
1
7
,
p
p
2
3
1
–
2
5
8
.
[3
5
]
Z.
Ya
n
,
N.
Jo
u
a
n
d
e
a
u
a
n
d
A
.
A
.
Ch
e
ri
f
,
“
A
S
u
rv
e
y
a
n
d
A
n
a
ly
sis
o
f
M
u
lt
i
-
Ro
b
o
t
C
o
o
r
d
in
a
ti
o
n
,
”
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
A
d
v
a
n
c
e
d
Ro
b
o
ti
c
S
y
ste
m
s,
2
3
Oc
t
2
0
1
3
,
S
a
in
t
-
De
n
is,
F
ra
n
c
e
.
[3
6
]
J.
F
a
ig
l
a
n
d
M
.
Ku
li
c
h
,
“
On
Be
n
c
h
m
a
r
k
in
g
o
f
F
ro
n
ti
e
r
-
Ba
se
d
M
u
lt
i
-
Ro
b
o
t
Ex
p
l
o
ra
ti
o
n
S
trate
g
ies
,
”
IEE
E
Eu
r
o
p
e
a
n
Co
n
f
e
re
n
c
e
o
n
M
o
b
il
e
R
o
b
o
ts
(E
CM
R),
2
-
4
S
e
p
2
0
1
5
,
L
in
c
o
l
n
,
U
K.
[3
7
]
S
.
Kim
,
S
.
Bh
a
tt
a
c
h
a
r
y
a
,
R.
G
h
r
ist
a
n
d
V
.
Ku
m
a
r,
“
T
o
p
o
lo
g
ica
l
Ex
p
lo
ra
ti
o
n
o
f
Un
k
n
o
w
n
a
n
d
P
a
rti
a
ll
y
Kn
o
w
n
En
v
iro
n
m
e
n
ts,
”
IEE
E/
RS
J
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
In
telli
g
e
n
t
Ro
b
o
ts
a
n
d
S
y
ste
m
s
(IROS),
3
-
7
No
v
2
0
1
3
.
T
o
k
y
o
,
Ja
p
a
n
.
[3
8
]
J.
Bu
tzk
e
a
n
d
M
.
L
ik
h
a
c
h
e
v
,
“
P
l
a
n
n
in
g
f
o
r
M
u
lt
i
-
Ro
b
o
t
Ex
p
lo
ra
t
io
n
w
it
h
M
u
lt
i
p
le
Ob
jec
ti
v
e
Util
it
y
F
u
n
c
ti
o
n
s,”
IEE
E/
RS
J I
n
tern
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
In
telli
g
e
n
t
Ro
b
o
ts
a
n
d
S
y
st
e
m
s,
2
5
-
3
0
S
e
p
2
0
1
1
,
S
a
n
F
ra
n
c
is
c
o
,
CA
,
USA
.
[3
9
]
J.
Ba
n
f
i·
A
.
Q.
L
i,
I.
Re
k
leiti
s,
F
.
Am
i
g
o
n
i,
N.
Ba
sili
c
o
,
“
S
trate
g
ies
f
o
r
Co
o
rd
in
a
ted
M
u
lt
ir
o
b
o
t
E
x
p
lo
ra
ti
o
n
w
it
h
Re
c
u
rre
n
t
Co
n
n
e
c
ti
v
it
y
Co
n
stra
i
n
ts,
”
S
p
rin
g
e
r,
S
c
ien
c
e
+
Bu
sin
e
ss
M
e
d
ia
i
n
A
u
to
n
o
m
o
u
s
R
o
b
o
ts
,
L
L
C,
2
3
J
u
n
2
0
1
7
,
p
p
1
-
20.
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