T
E
L
KO
M
N
I
KA
T
e
lec
om
m
u
n
icat
ion
,
Com
p
u
t
i
n
g,
E
lec
t
r
on
ics
an
d
Cont
r
ol
Vol.
18
,
No.
3
,
J
une
2020
,
pp.
146
7
~
14
74
I
S
S
N:
1693
-
6930
,
a
c
c
r
e
dit
e
d
F
ir
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a
de
by
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me
nr
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tekdikti
,
De
c
r
e
e
No:
21/E
/KP
T
/2018
DO
I
:
10.
12928/
T
E
L
KO
M
NI
KA
.
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1467
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60111
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E
mail:
muhammad_r
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.
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a
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id
1.
I
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RODU
C
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
3
,
J
une
2020:
146
7
-
14
74
1468
s
pe
c
t
r
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m
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W
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a
me
r
a
c
a
n
e
s
t
i
mat
e
th
e
a
c
t
ua
l
dis
tan
c
e
us
in
g
t
he
c
o
nc
e
pt
o
f
a
t
r
ia
ng
le
e
q
ua
ti
on
.
T
h
e
r
ob
o
t
op
e
r
a
t
i
ng
s
ys
te
m
(
R
O
S
)
is
ope
n
s
o
u
r
c
e
s
o
i
t
is
p
os
s
ib
le
t
o
p
r
oc
e
s
s
L
iDA
R
da
ta
s
o
th
a
t
it
c
a
n
p
r
od
uc
e
be
t
te
r
a
nd
m
or
e
a
c
c
u
r
a
te
ma
pp
i
ng
vis
ua
li
z
a
t
io
ns
.
T
h
us
,
th
is
r
o
bo
t
is
e
xp
e
c
ted
t
o
b
e
a
ble
t
o
p
r
o
vi
de
i
n
f
o
r
ma
ti
on
a
b
ou
t
t
he
map
o
f
t
he
r
o
o
m
i
n
r
e
a
l
-
t
im
e
.
M
ob
il
e
r
ob
ot
c
a
n
be
us
e
d
a
s
a
s
e
ns
o
r
no
de
a
nd
mo
ve
s
to
map
t
he
de
s
ir
e
d
a
r
e
a
[
14
]
.
Au
t
on
om
ous
v
e
h
ic
le
na
v
iga
ti
o
n
ha
s
b
e
c
o
me
a
n
i
mp
or
ta
nt
r
e
s
e
a
r
c
h
f
ie
lds
i
n
a
va
r
ie
ty
o
f
a
pp
l
ica
ti
ons
in
c
l
ud
in
g
n
a
v
iga
t
io
n
,
l
oc
a
li
z
a
ti
on
,
a
nd
ma
pp
in
g
[
1
5
,
16
]
.
T
he
i
nt
e
l
l
ige
nt
mo
b
il
e
r
ob
ots
r
e
qu
i
r
e
a
c
c
u
r
a
te
ma
ps
to
n
a
v
ig
a
te
the
i
r
e
n
vi
r
on
me
nt
.
S
im
u
lt
a
ne
ous
loc
a
l
iz
a
t
io
n
a
n
d
ma
pp
in
g
(
S
L
AM
)
h
a
s
be
c
o
me
t
he
m
os
t
p
r
io
r
it
y
a
s
a
m
a
p
pi
ng
me
t
ho
d
[
1
7
]
.
T
h
is
me
th
od
o
ve
r
c
om
e
s
the
p
r
ob
le
m
of
c
ons
t
r
uc
t
in
g
m
a
ps
in
u
n
kn
own
e
n
v
ir
on
me
nts
[
18
,
19]
.
S
L
AM
h
a
s
be
c
ome
a
n
e
s
s
e
nt
ia
l
tec
hn
ol
og
y
in
th
e
f
i
e
l
d
of
r
ob
o
ti
c
s
,
a
ut
o
ma
ti
on
a
nd
c
om
pu
te
r
v
is
i
on
.
A
mo
ng
t
he
va
r
io
us
s
e
ns
or
mo
da
l
it
ies
,
c
a
me
r
a
s
a
r
e
l
ow
c
os
t
a
n
d
p
r
o
vi
de
r
ic
h
vis
ua
l
a
nd
e
nv
i
r
o
nm
e
n
ta
l
i
n
f
o
r
mat
i
on
,
w
h
ich
ha
s
gr
ow
th
in
the
f
ut
u
r
e
[
2
0]
.
S
L
AM
is
the
c
ha
l
len
ge
o
f
p
lac
in
g
a
r
o
b
ot
a
t
a
n
u
n
kn
own
e
n
vi
r
on
me
nt
,
th
e
n
us
i
ng
th
e
o
nb
oa
r
d
s
e
ns
o
r
s
,
t
he
r
o
bo
t
c
ons
t
r
uc
ts
a
ma
p
o
f
th
e
s
u
r
r
ou
nd
in
gs
a
n
d
ut
il
iz
e
t
h
is
m
a
p
to
kn
ow
r
ob
ot
's
p
os
i
t
io
n
[
21
]
.
T
h
is
a
l
go
r
it
h
m
c
a
n
be
de
ve
lo
pe
d
f
o
r
ma
pp
in
g
th
e
a
g
r
ic
ul
tu
r
a
l
e
n
vi
r
on
me
nt
us
in
g
bo
th
a
c
a
m
e
r
a
a
n
d
a
l
a
s
e
r
s
c
a
n
ne
r
[
2
2
,
23]
.
T
h
e
r
e
a
r
e
ma
ny
wa
ys
t
o
r
e
p
r
e
s
e
nt
a
2D
e
n
vi
r
on
me
nt
,
in
wh
ic
h
t
he
oc
c
up
a
nc
y
g
r
id
is
t
he
mos
t
r
e
lev
a
n
t
me
t
ho
d
f
o
r
r
e
p
r
e
s
e
n
ti
ng
to
po
lo
g
ica
l
m
a
ps
,
l
i
ne
m
a
ps
,
a
nd
lan
d
ma
r
k
b
a
s
e
d
ma
ps
[
24
]
.
O
c
c
upa
nc
y
g
r
id
us
e
s
pr
ob
a
b
il
i
ty
va
lues
t
o
m
a
ke
mo
r
e
de
ta
i
led
ma
p
r
e
pr
e
s
e
nta
t
io
ns
.
E
a
c
h
c
e
l
l
i
n
t
he
oc
c
u
pa
n
c
y
g
r
id
h
a
s
a
v
a
l
ue
t
ha
t
r
e
p
r
e
s
e
nts
t
he
p
r
oba
b
il
it
y
o
f
t
he
c
e
l
l's
o
c
c
u
pa
nc
y
.
A
v
a
l
ue
c
l
os
e
t
o
1
r
e
p
r
e
s
e
nts
a
hi
gh
p
r
ob
a
b
il
i
ty
t
ha
t
th
e
r
e
is
a
n
obs
tac
le
.
M
e
a
nw
h
il
e
,
a
v
a
l
ue
c
los
e
to
0
in
di
c
a
tes
t
he
p
r
o
ba
bi
l
it
y
th
a
t
c
e
l
l
is
n
ot
o
c
c
up
ied
a
nd
is
f
r
e
e
o
f
o
bs
tac
les
.
Ac
c
u
r
a
te
ob
je
c
t
m
ode
l
in
g
is
a
n
in
te
r
e
s
t
in
g
c
ha
ll
e
n
ge
in
r
e
m
ot
e
s
e
ns
in
g
r
e
ga
r
d
in
g
w
i
th
t
he
L
iDA
R
p
oi
n
t
c
lo
ud
.
T
h
is
a
p
p
r
o
a
c
h
c
a
n
p
r
o
d
u
c
e
a
c
c
u
r
a
t
e
b
u
i
l
d
i
n
g
m
o
d
e
l
s
q
u
i
c
k
l
y
c
o
m
p
a
r
e
d
t
o
t
r
a
d
i
t
i
o
n
a
l
m
e
t
h
o
d
s
[
2
5
,
26]
.
L
i
D
A
R
-
b
a
s
e
d
S
L
A
M
c
o
m
b
i
n
e
s
p
o
s
i
t
i
o
n
i
n
g
a
n
d
m
a
p
p
i
n
g
i
n
v
o
l
v
i
n
g
m
u
l
t
i
p
l
e
c
o
n
s
e
c
u
t
i
v
e
s
c
a
n
p
o
i
n
t
f
r
a
m
e
s
o
r
s
c
a
n
m
a
t
c
h
i
n
g
[
9
]
.
L
o
c
a
l
i
z
a
t
i
o
n
u
s
i
n
g
s
c
a
n
m
a
t
c
h
i
n
g
g
e
n
e
r
a
l
l
y
i
n
v
o
l
v
e
s
t
h
e
i
t
e
r
a
t
i
v
e
c
l
o
s
e
s
t
p
o
i
n
t
(
I
C
P
)
a
l
g
o
r
i
t
h
m
.
T
h
e
I
C
P
i
s
a
m
e
t
h
o
d
u
s
e
d
t
o
m
i
n
i
m
i
z
e
t
h
e
d
i
f
f
e
r
e
n
c
e
b
e
t
w
e
e
n
t
w
o
-
p
o
i
n
t
c
l
o
u
d
.
T
h
e
m
e
t
h
o
d
i
s
b
a
s
e
d
o
n
p
o
i
n
t
c
l
o
u
d
s
e
g
m
e
n
t
a
t
i
o
n
u
s
e
d
t
o
r
e
d
u
c
e
p
r
o
c
e
s
s
i
n
g
t
i
m
e
f
o
l
l
o
w
e
d
b
y
g
r
o
u
p
i
n
g
.
T
h
i
s
a
l
g
o
r
i
t
h
m
i
s
o
f
t
e
n
u
s
e
d
t
o
r
e
c
o
n
s
t
r
u
c
t
t
h
e
s
u
r
f
a
c
e
o
f
t
h
e
s
c
a
n
r
e
s
u
l
t
s
f
o
r
r
o
b
o
t
n
a
v
i
g
a
t
i
o
n
p
u
r
p
o
s
e
s
.
R
a
s
p
be
r
r
y
P
i
3
M
ode
l
B
is
th
e
t
hi
r
d
g
e
ne
r
a
t
io
n
o
f
the
R
a
s
p
be
r
r
y
P
i
p
r
od
uc
t
.
W
it
h
s
mal
l
di
me
ns
i
ons
a
n
d
h
i
gh
c
om
pu
t
in
g
c
a
pa
b
i
li
ty
,
th
is
d
e
ve
l
op
men
t
b
oa
r
d
is
w
id
e
l
y
us
e
d
in
s
in
gle
-
bo
a
r
d
c
om
pu
te
r
(
S
B
C
)
ba
s
e
d
r
ob
ots
.
T
h
e
op
e
r
a
t
i
ng
s
ys
te
m
o
f
th
e
R
a
s
p
be
r
r
y
P
i
3
M
ode
l
B
is
bo
ote
d
t
h
r
o
ug
h
a
mi
c
r
o
S
D
c
a
r
d
a
nd
r
u
ns
wi
th
va
r
io
us
o
pe
r
a
t
in
g
s
ys
te
ms
,
s
uc
h
a
s
Ub
un
t
u
,
W
i
nd
ows
1
0
I
o
T
,
R
a
s
pb
ia
n
S
t
r
e
c
h
,
No
ob
a
nd
ot
he
r
s
.
T
h
is
S
B
C
ha
s
a
B
r
oa
d
c
o
m
B
C
M
28
37
s
ys
te
m
,
a
n
AR
M
C
o
r
t
e
x
-
A5
3
64
-
bi
t
Qua
d
C
o
r
e
P
r
o
c
e
s
s
or
w
it
h
a
s
p
e
e
d
o
f
1
.
2
GH
z
.
T
h
e
R
a
s
pb
e
r
r
y
P
i
3
m
ode
l
B
ha
s
4
0
I
/
O
p
ins
,
1
GB
o
f
R
AM
,
4
US
B
p
or
ts
,
80
2
.
1
1
w
ir
e
l
e
s
s
L
AN
,
b
lue
to
o
th
lo
w
e
ne
r
g
y
4
.
1
,
a
n
H
DM
I
c
o
nn
e
c
to
r
a
nd
a
3
.
5
m
m
a
udi
o
c
on
ne
c
t
o
r
[
27
]
.
T
he
R
a
s
p
be
r
r
y
P
i
is
de
s
ig
ne
d
l
ike
a
S
B
C
m
o
du
le
s
o
t
ha
t
i
t
c
a
n
be
c
a
l
le
d
a
mi
ni
c
o
mp
u
te
r
.
T
o
b
e
a
c
c
e
s
s
ib
le
,
th
e
R
a
s
pb
e
r
r
y
P
i
mus
t
be
c
on
ne
c
te
d
t
o
ot
he
r
n
e
c
e
s
s
a
r
y
p
e
r
i
ph
e
r
a
ls
s
uc
h
a
s
a
m
on
it
o
r
s
c
r
e
e
n
(
via
H
DM
I
)
a
n
d
i
np
ut
/o
ut
pu
t
d
e
v
ice
s
s
uc
h
a
s
a
ke
ybo
a
r
d
a
nd
m
o
us
e
[
2
8
]
.
2.
RE
S
E
AR
CH
M
E
T
HO
D
F
igur
e
1
s
hows
the
s
c
he
me
of
the
ove
r
a
ll
s
ys
tem
us
e
d
in
the
e
xpe
r
im
e
nt
a
nd
block
diagr
a
m
of
the
r
oboti
c
s
ys
tem.
T
he
YD
L
iDAR
X4
s
e
ns
or
is
us
e
d
a
s
a
n
indoor
2D
s
c
a
nne
r
.
T
he
wor
king
pr
inciple
of
thi
s
s
e
ns
or
us
e
s
the
tr
iangula
ti
on
method
in
de
te
r
mi
ning
the
dis
tanc
e
of
the
objec
t
.
T
he
L
iDAR
us
e
s
a
las
e
r
that
mee
ts
F
DA
c
las
s
1
s
tanda
r
ds
.
T
his
s
e
ns
or
is
e
q
uipped
with
a
dc
mot
o
r
s
o
that
it
c
a
n
pe
r
f
or
m
360
s
c
a
nning.
T
he
r
e
s
ult
s
of
the
s
c
a
n
a
r
e
a
ngular
va
lu
e
s
a
long
wi
th
the
dis
tanc
e
of
the
objec
t.
T
he
S
B
C
of
R
a
s
pbe
r
r
y
P
i
3
B
is
us
e
d
to
a
c
c
e
s
s
the
L
iDAR
s
e
n
s
or
.
T
he
L
iDAR
da
ta
is
then
s
e
nt
to
the
c
omput
e
r
wir
e
les
s
ly
to
be
pr
oc
e
s
s
e
d
int
o
a
map.
T
his
c
omput
e
r
a
nd
S
B
C
a
r
e
int
e
gr
a
ted
in
the
R
OS
.
Dis
tanc
e
da
ta
c
oll
e
c
ti
on
f
r
om
L
iDAR
mea
s
ur
e
ments
will
be
c
om
pa
r
e
d
with
the
a
c
tual
dis
tanc
e
to
f
ind
out
it
s
a
c
c
ur
a
c
y.
T
he
moveme
nt
of
the
r
obo
t
c
a
n
us
e
manua
l
c
ontr
ol
or
a
utom
a
ti
c
na
vigation
to
e
xplor
e
the
r
oom
.
T
he
c
o
mm
a
nds
f
or
the
r
obot
moveme
nt
c
ome
f
r
om
S
B
C
via
the
Ar
duino
Na
no
mi
c
r
oc
ont
r
oll
e
r
.
T
he
L
iDAR
da
t
a
wi
ll
be
pr
oc
e
s
s
e
d
on
the
s
c
a
n
matc
hing
to
obtain
tr
a
ns
f
or
mation
o
f
the
pos
it
ion
a
nd
the
r
otation
wi
tho
ut
whe
e
l
odometr
y
da
ta.
T
his
S
c
a
n
M
a
tching
r
e
s
ult
is
a
n
e
s
ti
mate
of
the
pos
it
ion
a
nd
o
r
ienta
ti
on
o
f
the
r
obot
.
P
r
oba
bil
it
y
c
a
lcula
ti
ons
a
r
e
then
ne
e
de
d
to
d
e
ter
mi
ne
the
va
lue
of
e
a
c
h
g
r
id.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
2D
mapping
us
ing
omni
-
dir
e
c
ti
onal
mobi
le
r
obot
e
quipped
w
it
h
L
iDA
R
(
M
uhamm
ad
R
ivai)
1469
D
i
s
ta
n
c
e
Ma
n
u
a
l
/
A
u
t
o
C
om
m
a
n
d
Ma
n
u
a
l
/
A
u
to
D
a
ta
L
i
D
A
R
D
a
t
a
PW
M
Vo
l
ta
g
e
(
a
)
(
b)
F
igur
e
1.
(
a
)
S
c
he
me
o
f
the
r
oboti
c
s
ys
tem,
(
b)
B
lock
diagr
a
m
of
the
r
oboti
c
s
ys
tem
T
he
r
obot
is
de
s
igned
us
ing
3
omni
-
whe
e
ls
a
nd
12
V
DC
mot
or
s
whic
h
e
a
c
h
whe
e
l
is
s
e
pa
r
a
ted
by
12
0
de
gr
e
e
s
,
s
hown
in
F
igur
e
2.
T
he
mot
o
r
s
pe
e
d
is
c
ontr
oll
e
d
us
ing
a
pr
opor
ti
ona
l
-
int
e
gr
a
l
-
de
r
ivative
(
P
I
D)
method
to
f
oll
ow
the
wa
ll
.
T
he
wa
ll
f
oll
owing
met
hod
ha
s
r
e
c
e
ntl
y
be
c
ome
a
n
int
e
r
e
s
ti
ng
top
ic
whic
h
c
a
n
he
lp
na
vigate
r
obots
in
a
mes
s
y
or
dis
or
de
r
ly
e
nvi
r
onment
[
29
,
30]
.
T
he
r
obot
tr
a
ve
ls
a
long
c
ontour
o
f
the
objec
t
with
a
c
e
r
tain
dis
tanc
e
.
T
his
s
tr
a
tegy
c
a
n
be
ve
r
y
he
lp
f
ul
whe
n
a
r
obot
is
s
tuck
in
a
de
a
dl
oc
k
[
31]
.
T
he
output
of
a
c
ontr
ol
s
ignal
is
a
puls
e
width
modul
a
ti
on
(
P
W
M
)
s
ignal.
T
o
ge
ne
r
a
te
a
P
W
M
s
ignal,
the
Ana
logWr
it
e
(
)
f
unc
ti
on
is
us
e
d
on
the
A
r
duino
Na
no
mi
c
r
oc
ontr
ol
ler
.
T
he
He
c
tor
S
L
AM
a
lgor
it
hm
de
ter
mi
ne
s
the
p
os
it
ion
of
the
r
obot
ba
s
e
d
on
S
c
a
n
M
a
tching.
T
he
He
c
tor
S
L
AM
a
lgor
it
hm
us
e
s
the
Ga
us
s
ian
-
N
e
wton
mi
nim
iza
ti
on
method
whic
h
is
c
ons
ider
e
d
t
o
r
e
plac
e
the
Ne
wton
method.
T
he
L
iDAR
da
ta
will
be
us
e
d
to
de
ter
mi
ne
the
obs
tac
les
e
nc
ounter
e
d
by
the
r
obo
t.
T
he
s
e
obs
tac
les
will
be
r
e
pr
e
s
e
nted
in
Oc
c
upa
nc
y
Gr
id
mapping.
I
n
He
c
tor
S
L
AM
,
to
de
ter
mi
ne
oc
c
upa
n
c
y
in
the
gr
id,
log
-
odds
pr
oba
bil
i
ti
e
s
that
f
ol
low
the
r
ules
of
p
r
oba
bil
it
y
o
f
B
a
ye
s
a
r
e
us
e
d.
B
a
ye
s
pr
oba
b
il
it
y
is
a
r
e
c
ur
s
ive
pr
oba
bil
it
y
c
a
lcula
ti
on
that
invol
ve
s
the
va
lue
o
f
the
pr
e
vious
c
a
lcula
ti
on.
I
f
(
,
)
i
s
the
pr
oba
bil
it
y
of
gr
id
oc
c
upa
nc
y
a
t
the
c
oo
r
dinate
s
x
a
nd
y,
(
)
is
the
pr
oba
bil
it
y
of
mea
s
ur
ing
L
iDAR
[
22]
,
then
the
pr
oba
bil
it
y
e
q
ua
ti
on
ba
s
e
d
o
n
B
a
ye
s
is
:
(
,
|
)
=
(
|
,
)
(
,
)
(
)
(
1)
B
a
ye
s
ian
e
qua
ti
ons
f
or
the
pr
oba
bil
it
y
of
gr
id
oc
c
upa
nc
y
whe
n
the
p
r
e
s
e
nc
e
or
a
bs
e
nc
e
of
obs
tac
les
c
a
n
be
e
xpr
e
s
s
e
d
a
s
:
(
,
=
1
|
)
=
(
|
,
=
1
)
(
,
=
1
)
(
)
(
2)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
3
,
J
une
2020:
146
7
-
14
74
1470
(
,
=
0
|
)
=
(
|
,
=
0
)
(
,
=
0
)
(
)
(
3)
T
o
make
the
e
qua
ti
on
of
log
-
odds
pr
oba
bil
it
y,
the
odd
f
or
mul
a
is
us
e
d
f
ir
s
t
to
c
a
lcula
te
the
r
a
ti
o
of
the
pr
oba
bil
it
y
of
the
map:
=
(
4)
=
(
,
=
1
|
)
(
,
=
0
|
)
(
5)
F
r
om
(
2
)
,
(
3
)
a
nd
(
5)
,
we
ge
t
the
f
o
ll
owing
e
qua
ti
o
n:
log
=
log
(
,
=
1
|
)
(
,
=
0
|
)
=
log
(
|
,
=
1
)
(
,
=
1
)
(
|
,
=
0
)
(
,
=
0
)
=
log
(
|
,
=
1
)
(
|
,
=
0
)
+
log
(
,
=
1
)
(
,
=
0
)
(
6)
l
og
+
=
log
m
e
a
s
u
r
e
m
e
nt
+
log
−
(
7)
I
f
the
pos
it
ion
of
the
r
obot
is
=
(
,
,
)
then
to
ge
t
the
c
oor
di
na
tes
of
the
obs
tac
les
a
t
dis
tanc
e
d
a
r
e
:
[
]
=
[
co
s
−
s
in
s
in
co
s
]
[
0
]
+
[
]
(
8)
(
a
)
Wa
l
l
y
(
b)
(
c
)
F
igur
e
2.
(
a
)
De
s
ign
of
the
omni
-
whe
e
l
mot
or
dr
iv
e
r
s
,
(
b)
W
a
ll
-
f
oll
ow
ing
r
obo
t,
(
c
)
B
lock
diagr
a
m
of
the
P
I
D
c
ontr
ol
3.
RE
S
UL
T
S
A
ND
AN
AL
YSI
S
3.
1.
T
h
e
YD
L
iDAR
X4
s
e
n
s
or
m
e
as
u
r
e
m
e
n
t
I
n
thi
s
e
xpe
r
im
e
nt,
a
r
a
nge
of
L
iDAR
s
e
ns
or
wa
s
mea
s
ur
e
d.
T
a
ble
1
s
hows
the
r
e
s
ult
s
of
dis
tanc
e
mea
s
ur
e
ments
by
the
L
iDAR
with
a
r
a
nge
be
twe
e
n
0.
5
-
12.
5
m
whe
r
e
the
a
ve
r
a
ge
e
r
r
or
r
a
te
is
1.
1%
.
T
his
indi
c
a
tes
that
the
s
e
ns
or
c
a
n
be
us
e
d
to
ma
p
a
r
oom.
T
he
L
iDAR
c
a
nnot
mea
s
ur
e
dis
tanc
e
s
g
r
e
a
ter
than
10.
5
m.
3.
2.
Wall
-
f
oll
owin
g
r
ob
ot
I
n
thi
s
e
xpe
r
im
e
nt,
the
r
e
s
pons
e
of
the
r
obot
wa
s
mea
s
ur
e
d
to
maintain
the
dis
tanc
e
to
the
wa
ll
us
in
g
P
I
D
c
ontr
ol
.
T
he
P
I
D
pa
r
a
mete
r
s
a
r
e
obtaine
d
by
manua
l
tuni
ng
method
whe
r
e
the
va
lue
o
f
kp
is
20
,
ki
is
0
,
a
nd
kd
is
1000.
F
igu
r
e
3
s
hows
that
the
moveme
n
t
of
the
r
obot
in
f
ol
lowing
the
wa
ll
is
quit
e
good
e
ve
n
though
ther
e
is
a
s
tea
dy
s
tate
e
r
r
or
.
T
he
pur
pos
e
o
f
thi
s
c
ontr
ol
is
to
ke
e
p
the
r
obot
in
the
L
iDAR
mea
s
ur
e
me
nt
r
a
nge
a
nd
to
mi
nim
ize
c
ha
nge
s
in
the
moveme
nt
o
f
th
e
r
obot.
L
a
r
ge
c
ha
nge
s
in
moveme
nt
wi
ll
r
e
s
ult
e
r
r
or
s
in
mapping.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
2D
mapping
us
ing
omni
-
dir
e
c
ti
onal
mobi
le
r
obot
e
quipped
w
it
h
L
iDA
R
(
M
uhamm
ad
R
ivai)
1471
T
a
ble
1.
Dis
tanc
e
mea
s
ur
e
ment
by
the
L
iDAR
A
c
tu
a
l
di
s
ta
nc
e
(
m)
M
e
a
s
ur
e
d di
s
ta
nc
e
(
m)
E
r
r
or
(%)
0.5
0.510
2
1.5
1.518
1.2
2.5
2.509
0.36
3.5
3.517
0.48
4.5
4.531
0.68
5.5
5.525
0.45
6.5
6.561
0.93
7.5
7.606
1.4
8.5
8.600
1.17
9.5
9.679
1.88
10.5
10.662
1.54
11.5
0
-
12.5
0
-
A
ve
r
a
ge
e
r
r
or
1.1
F
igur
e
3.
R
e
s
pons
e
of
wa
ll
-
f
oll
owing
r
obot
us
ing
P
I
D
c
ontr
ol
3.
3.
Robot
p
os
it
ion
u
s
in
g
s
c
an
m
at
c
h
i
n
g
T
he
He
c
tor
S
L
AM
method
is
us
e
d
to
de
ter
mi
ne
th
e
pos
it
ion
o
f
the
r
obo
t
wi
thout
the
whe
e
l
odometr
y
but
ins
tea
d
us
e
s
s
c
a
n
mat
c
hing.
I
n
thi
s
e
xpe
r
im
e
nt,
a
c
ompar
is
on
wa
s
made
be
twe
e
n
the
a
c
tual
r
obot
pos
it
ion
a
nd
the
r
e
s
ult
s
of
S
c
a
n
M
a
tching.
T
his
e
x
pe
r
im
e
nt
i
s
c
a
r
r
ied
out
by
r
unning
the
r
ob
ot
with
the
ke
yboa
r
d
c
ontr
ol
a
s
f
a
r
a
s
the
s
pe
c
if
ied
dis
tanc
e
,
a
s
s
hown
in
F
igur
e
4.
B
a
s
e
d
on
T
a
ble
2,
the
a
ve
r
a
ge
e
r
r
or
s
in
the
x
-
a
xis
a
nd
y
-
a
xis
a
r
e
2.
69%
,
a
nd
5
.
11%
,
r
e
s
pe
c
ti
ve
ly,
(
or
the
tot
a
l
e
r
r
or
r
a
te
of
3.
9%
)
.
B
e
c
a
us
e
the
pos
it
ion
of
He
c
tor
S
L
AM
invol
ve
s
th
e
S
c
a
n
M
a
tching
method,
the
e
r
r
or
f
r
om
the
L
iDA
R
s
e
ns
or
will
a
f
f
e
c
t
the
pos
it
ion
o
f
the
r
obot.
(
a
)
(
b)
F
igur
e
4
.
(
a
)
M
e
a
s
ur
e
ment
o
f
pos
it
ion
da
ta,
(
b)
Oc
c
upa
nc
y
g
r
id
tes
ti
ng
T
a
ble
2.
P
os
it
ion
o
f
the
r
obot
us
ing
s
c
a
n
m
a
tching
A
c
tu
a
l
pos
it
io
n (
m)
M
e
a
s
ur
e
d po
s
it
io
n (
m)
E
r
r
or
(
%
)
X
Y
X
Y
X
Y
0.25
0.25
0.26
0.23
4
8
0.50
0.50
0.52
0.42
4
16
0.75
0.75
0.76
0.73
1.3
2.6
1.00
1.00
0.98
0.96
2
4
1.25
1.25
1.23
1.23
1.6
1.6
1.50
1.50
1.42
1.45
5.3
3.3
1.75
1.75
1.71
1.70
2.2
2.8
2.00
2.00
1.98
1.95
1
2.5
A
ve
r
a
ge
e
r
r
or
2.69
5.11
3.
4.
Room
m
ap
p
in
g
T
he
S
L
AM
a
lgo
r
it
hm
is
us
e
d
to
c
ons
tr
uc
t
unknow
n
e
nvir
onment
map
while
s
im
ult
a
ne
ous
ly
t
r
a
c
king
the
loca
ti
on
o
f
the
r
obot
wi
thi
n
it
.
T
he
r
e
f
or
e
,
it
is
ne
c
e
s
s
a
r
y
to
us
e
gr
ound
tr
u
th
to
ve
r
i
f
y
the
e
s
ti
mation
r
e
s
ult
s
[
32]
.
I
n
thi
s
e
xpe
r
im
e
nt,
we
us
e
a
model
r
o
om
that
ha
s
a
s
ize
of
2
.
4
m
x
2
.
4
m
a
nd
then
c
a
r
r
i
e
d
out
a
tr
ial
in
a
r
e
a
l
r
oom
with
a
s
ize
of
12
m
x
8.
4
m,
a
s
the
gr
ound
tr
uths
.
R
oom
mapping
c
a
n
be
c
a
r
r
i
e
d
out
by
r
unning
the
mobi
le
r
obo
t
wir
e
les
s
ly
via
a
ke
yboa
r
d
on
a
laptop
(
manua
l
mode)
.
T
his
mapping
is
a
ls
o
c
a
r
r
ied
out
by
r
unning
the
mobi
le
r
obot
a
utom
a
ti
c
a
ll
y
to
e
xplor
e
the
r
oom
by
f
oll
owing
the
wa
ll
(
a
utom
a
ti
c
mode)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
3
,
J
une
2020:
146
7
-
14
74
1472
T
he
L
iDA
R
da
ta
is
then
s
e
nt
to
the
c
omput
e
r
to
be
pr
oc
e
s
s
e
d
a
nd
dis
playe
d
us
ing
the
r
v
iz
tool
s
.
All
da
ta
c
oll
e
c
ted
dur
ing
mapping
thi
s
r
oom
is
s
tor
e
d
in
a
r
os
ba
g.
I
n
the
f
i
r
s
t
e
xpe
r
im
e
nt,
the
r
obot
is
r
un
a
uto
matica
ll
y
in
tr
a
c
ing
the
e
nti
r
e
r
oom
a
c
c
or
ding
to
the
d
e
s
ign
in
F
igu
r
e
5
.
T
a
ble
3
s
how
a
n
a
ve
r
a
ge
e
r
r
or
r
a
te
of
5.
32
%
.
T
he
las
t
e
xpe
r
im
e
nt
wa
s
c
a
r
r
ied
out
in
a
r
e
a
l
r
oo
m,
a
s
s
hown
in
F
igu
r
e
6
.
I
t
s
hows
that
the
move
ment
of
the
r
obot
manua
ll
y
a
nd
a
utom
a
ti
c
a
ll
y
ha
s
mea
s
ur
e
ment
e
r
r
or
r
a
te
o
f
4
.
00%
,
a
nd
4.
59%
,
r
e
s
pe
c
ti
ve
ly.
T
his
indi
c
a
tes
that
the
omni
-
dir
e
c
ti
ona
l
mobi
l
e
r
obot
e
quipped
with
L
iDAR
is
a
ble
to
ma
ke
r
oom
maps
a
utom
a
ti
c
a
ll
y.
(
a
)
(
b)
F
igur
e
5.
(
a
)
De
s
ign
of
the
e
xpe
r
im
e
ntal
model
r
oo
m,
(
b
)
R
e
s
ult
of
mapping
T
a
ble
3.
S
ize
of
mapping
r
e
s
ult
in
the
e
xpe
r
im
e
nt
W
a
ll
in
de
x
A
c
tu
a
l
w
a
ll
le
ngt
h (
m)
M
e
a
s
ur
e
d w
a
ll
le
ngt
h (
m)
E
r
r
or
(
%
)
A
2.4
2.32
3.33
B
2.4
2.38
0.83
C
0.25
0.26
4.00
D
0.53
0.55
3.77
E
0.74
0.88
18.91
F
0.74
0.75
1.35
G
0.44
0.43
2.27
H
0.58
0.65
12,06
I
0.74
0.73
1,35
A
ve
r
a
ge
e
r
r
or
(
%
)
5.32
(
a
)
(
b)
(
c
)
F
igur
e
6.
(
a
)
T
he
a
c
tual
r
oom
,
(
b)
M
a
p
r
e
s
ult
e
d
in
the
a
utom
a
ti
c
mode,
(
c
)
M
a
p
r
e
s
ult
e
d
in
the
manua
l
mode
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
2D
mapping
us
ing
omni
-
dir
e
c
ti
onal
mobi
le
r
obot
e
quipped
w
it
h
L
iDA
R
(
M
uhamm
ad
R
ivai)
1473
4.
CONC
L
USI
ON
I
n
t
hi
s
s
tu
dy
,
a
n
o
mn
i
-
d
i
r
e
c
t
io
na
l
m
ob
i
le
r
ob
ot
e
qu
ip
pe
d
wi
th
a
L
iD
AR
s
e
ns
o
r
h
a
s
be
e
n
de
ve
l
op
e
d
f
or
m
a
p
p
in
g
a
r
oo
m
.
T
he
Y
DL
i
DA
R
X
4
s
e
ns
o
r
is
us
e
d
a
s
a
n
i
nd
oo
r
2D
s
c
a
n
ne
r
.
T
he
S
B
C
o
f
R
a
s
p
be
r
r
y
P
i
3
B
is
u
s
e
d
to
a
c
c
e
s
s
t
he
L
i
DA
R
s
e
ns
o
r
.
T
h
e
L
iD
AR
da
ta
i
s
th
e
n
s
e
nt
to
t
he
c
om
pu
te
r
w
i
r
e
l
e
s
s
l
y
t
o
be
p
r
oc
e
s
s
e
d
i
nt
o
a
m
a
p
.
T
h
is
c
om
pu
te
r
a
nd
S
B
C
a
r
e
in
te
gr
a
t
e
d
in
R
O
S
.
T
he
mo
ve
men
t
of
t
he
r
o
bo
t
c
a
n
us
e
ma
nua
l
c
o
n
tr
o
l
o
r
a
ut
o
mat
ic
n
a
v
iga
t
io
n
to
e
x
pl
o
r
e
t
he
r
oo
m
.
T
he
c
om
ma
nds
f
o
r
th
e
r
o
bo
t
m
ove
me
nt
c
ome
f
r
o
m
S
B
C
vi
a
t
he
A
r
d
ui
no
Na
no
m
ic
r
oc
o
nt
r
ol
le
r
.
T
he
He
c
to
r
S
L
AM
a
lg
or
i
th
m
d
e
t
e
r
m
in
e
s
t
he
po
s
i
ti
on
o
f
th
e
r
o
bo
t
b
a
s
e
d
o
n
S
c
a
n
M
a
t
c
h
in
g
o
f
th
e
L
iDA
R
da
t
a
.
T
he
da
ta
is
u
s
e
d
to
de
te
r
mi
ne
t
he
o
bs
t
a
c
les
e
n
c
o
un
te
r
e
d
by
t
he
r
obo
t
.
T
he
s
e
o
bs
tac
les
w
il
l
be
r
e
p
r
e
s
e
n
te
d
in
Oc
c
u
pa
n
c
y
G
r
id
map
p
in
g
.
T
he
e
x
pe
r
i
me
nt
a
l
r
e
s
u
l
ts
s
ho
w
tha
t
t
he
L
iD
AR
s
e
ns
o
r
h
a
s
a
me
a
s
u
r
e
me
nt
r
a
n
ge
o
f
0
.
1
2
-
1
0
.
5
m
.
T
he
r
ob
ot
is
a
b
le
to
f
ol
lo
w
t
he
wa
ll
us
i
ng
P
I
D
c
on
t
r
o
l.
T
h
e
S
c
a
n
M
a
t
c
h
in
g
me
t
ho
d
is
a
bl
e
t
o
p
r
e
di
c
t
th
e
pos
it
io
n
o
f
the
r
ob
ot
w
i
th
a
n
e
r
r
o
r
r
a
te
o
f
3
.
9
%
.
E
x
pe
r
i
m
e
n
t
i
n
t
he
mo
de
l
r
oo
m
,
t
he
r
ob
ot
c
a
n
b
ui
l
d
ma
ps
wi
th
a
n
e
r
r
o
r
r
a
t
e
o
f
6
.
4
4
%
.
W
h
e
r
e
a
s
,
e
xpe
r
im
e
n
t
i
n
a
c
tua
l
r
oo
m
,
t
he
r
ob
o
t
c
a
n
mo
ve
a
ut
o
mat
ic
a
l
ly
t
o
c
ons
t
r
uc
t
map
s
w
it
h
a
n
e
r
r
o
r
r
a
te
o
f
4
.
5
9%
.
T
he
s
e
r
e
s
ul
ts
in
dic
a
t
e
t
ha
t
t
he
m
ob
il
e
r
o
bo
t
e
qu
ip
pe
d
wi
t
h
L
i
DA
R
a
r
e
a
ble
to
b
ui
ld
ma
ps
a
c
c
u
r
a
te
ly
.
F
o
r
f
u
tu
r
e
wo
r
k
,
we
wi
l
l
d
e
v
e
l
op
t
h
r
e
e
-
d
im
e
ns
io
na
l
m
a
p
pi
ng
us
in
g
a
m
ob
i
le
r
obo
t
a
c
c
om
pa
ni
e
d
b
y
L
i
DA
R
t
o
s
e
a
r
c
h
f
o
r
v
ict
im
s
in
a
c
ol
la
ps
e
d
b
ui
ld
i
ng
.
AC
KNOWL
E
DGE
M
E
NT
S
T
his
r
e
s
e
a
r
c
h
wa
s
c
a
r
r
ied
out
with
f
inanc
ial
a
id
s
u
ppor
t
f
r
om
the
M
ini
s
tr
y
o
f
R
e
s
e
a
r
c
h,
T
e
c
hnology
a
nd
Highe
r
E
duc
a
ti
on
o
f
the
R
e
publi
c
of
I
ndon
e
s
ia
(
Ke
menr
is
tekdikti
R
I
)
a
nd
L
e
mbaga
P
e
ne
li
t
ian
da
n
P
e
nga
bdian
Ke
pa
da
M
a
s
ya
r
a
ka
t
(
L
P
P
M
)
I
ns
ti
tut
T
e
knologi
S
e
puluh
Nope
mber
(
I
T
S
)
S
ur
a
ba
ya
.
RE
F
E
RE
NC
E
S
[1
]
O
.
V
y
s
o
t
s
k
a
an
d
C.
St
ac
h
n
i
s
s
,
“
E
x
p
l
o
i
t
i
n
g
b
u
i
l
d
i
n
g
i
n
fo
rma
t
i
o
n
fr
o
m
p
u
b
l
i
c
l
y
a
v
ai
l
ab
l
e
ma
p
s
i
n
g
rap
h
-
b
a
s
e
d
SL
A
M
,
”
IE
E
E
In
t
er
n
a
t
i
o
n
a
l
C
o
n
f
er
e
n
ce
o
n
I
n
t
e
l
l
i
g
e
n
t
R
o
b
o
t
s
a
n
d
S
ys
t
em
s
,
p
p
.
4
5
1
1
-
4
5
1
6
,
2
0
1
6
.
[2
]
D
.
Sh
en
,
et
al
.
, “
Res
earch
an
d
Imp
l
emen
t
at
i
o
n
o
f
SL
A
M
Bas
ed
o
n
L
ID
A
R
fo
r
Fo
u
r
-
W
h
eel
e
d
Mo
b
i
l
e
Ro
b
o
t
,”
IE
E
E
In
t
e
r
n
a
t
i
o
n
a
l
Co
n
f
er
e
n
ce
o
n
In
t
e
l
l
i
g
e
n
t
R
o
b
o
tic
a
n
d
C
o
n
t
r
o
l
E
n
g
i
n
eer
i
n
g
,
p
p
.
19
-
23
,
2
0
1
8
.
[3
]
M.
G
.
O
can
d
o
,
et
al
.
,
“
A
u
t
o
n
o
mo
u
s
2
D
SL
A
M
a
n
d
3
D
Map
p
i
n
g
o
f
a
n
E
n
v
i
ro
n
men
t
U
s
i
n
g
a
S
i
n
g
l
e
2
D
L
ID
A
R
an
d
RO
S,
”
2
0
1
7
La
t
in
Am
e
r
i
ca
n
R
o
b
o
t
i
c
s
S
y
m
p
o
s
i
u
m
a
n
d
2
0
1
7
B
r
a
z
i
l
i
a
n
S
y
m
p
o
s
i
u
m
o
n
R
o
b
o
t
i
c
s
,
p
p
.
2
-
7
,
N
o
v
2
0
1
7
.
[4
]
D
.
G
h
o
rp
ad
e,
et
al
.
,
“
O
b
s
t
ac
l
e
D
et
ec
t
i
o
n
an
d
A
v
o
i
d
an
ce
A
l
g
o
r
i
t
h
m
fo
r
A
u
t
o
n
o
m
o
u
s
Mo
b
i
l
e
Ro
b
o
t
u
s
i
n
g
2
D
L
i
D
A
R
,
”
In
t
e
r
n
a
t
i
o
n
a
l
Co
n
f
er
e
n
ce
o
n
Co
m
p
u
t
i
n
g
,
Co
m
m
u
n
i
ca
t
i
o
n
,
Co
n
t
r
o
l
a
n
d
A
u
t
o
m
a
t
i
o
n
,
p
p
.
1
-
6
,
2
0
1
8
.
[5
]
P.
Mi
ro
w
s
k
i
,
et
a
l
.
,
“
D
e
p
t
h
camera
SL
A
M
o
n
a
l
o
w
-
co
s
t
W
i
F
i
map
p
i
n
g
r
o
b
o
t
,
”
I
E
E
E
In
t
er
n
a
t
i
o
n
a
l
Co
n
f
e
r
en
c
e
o
f
Tech
n
o
l
o
g
i
es
f
o
r
P
r
a
ct
i
ca
l
R
o
b
o
t
A
p
p
l
i
c
a
t
i
o
n
,
p
p
.
1
-
6
,
2
0
1
2
.
[6
]
D
.
H
an
,
et
al
.
,
“D
y
n
am
i
c
o
b
s
t
ac
l
e
av
o
i
d
an
ce
f
o
r
man
i
p
u
l
at
o
rs
u
s
i
n
g
d
i
s
t
a
n
ce
cal
cu
l
at
i
o
n
an
d
d
i
s
cret
e
d
et
ec
t
i
o
n
,
”
R
o
b
o
t
i
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.
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al
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2
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.
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4
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p
.
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5
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R.
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at
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as
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al
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[1
6
]
P.
Mari
n
-
p
l
aza,
et
al
.
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o
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L
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[1
7
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M.
Mu
s
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afa,
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t
al
.
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[1
8
]
J
.
L
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,
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al
.
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“SL
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[1
9
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J
.
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.
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“
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
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T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
3
,
J
une
2020:
146
7
-
14
74
1474
[2
0
]
X
i
a
o
L.
,
et
al
.
,
“D
y
n
ami
c
-
SL
A
M
:
Sema
n
t
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c
Mo
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o
c
u
l
ar
V
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s
u
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l
L
o
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i
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n
d
Map
p
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n
g
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s
ed
o
n
D
ee
p
L
earn
i
n
g
i
n
D
y
n
am
i
c
E
n
v
i
ro
n
men
t
,
”
R
o
b
o
t
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c
s
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n
d
A
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m
s
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l
.
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1
7
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,
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[2
1
]
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.
A
.
D
ao
u
d
,
et
al
.
,
“SL
A
MM:
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s
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al
Mo
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ar
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l
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Map
s
,
”
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S
,
p
p
.
1
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.
[2
2
]
F.
A
.
Ch
eei
n
,
et
a
l
.
,
“O
p
t
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mi
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d
E
IF
-
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l
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s
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re
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.
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,
p
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.
1
9
5
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2
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1
.
[2
3
]
D
.
Rei
s
er,
et
al
.
,
“It
erat
i
v
e
In
d
i
v
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d
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al
Pl
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Cl
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l
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.
4
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,
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2
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.
[2
4
]
E
.
H
o
rv
a
t
h
an
d
C.
R.
Po
zn
a,
“Pro
b
ab
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ccu
p
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ri
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o
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,
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p
.
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-
5
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2
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.
[2
5
]
T
azi
r
M.
L
.
,
et
al
.
,
“CICP:
Cl
u
s
t
er
It
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v
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A
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y
s
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u
l
2
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.
[2
6
]
A
.
M.
Rami
y
a,
et
a
l
.
,
“Seg
men
t
at
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o
n
Bas
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Bu
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o
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p
.
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6
.
[2
7
]
E
b
e
n
U
.
an
d
G
aret
h
H
.
,
“
Ras
p
b
erry
Pi
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s
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u
i
d
e
,
”
Fi
r
s
t
E
d
i
t
.
J
o
h
n
W
i
l
e
y
&
So
n
s
L
t
d
,
2
0
1
6
.
[2
8
]
M.
Ri
v
ai
,
et
a
l
.
,
“Meat
Fres
h
n
e
s
s
Id
e
n
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fi
cat
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as
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ra
l
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t
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,
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o
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Th
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