I
nte
rna
t
io
na
l J
o
urna
l o
f
Ro
bo
t
ics a
nd
Aut
o
m
a
t
io
n
(
I
J
RA
)
Vo
l.
4
,
No
.
4
,
Dec
em
b
er
201
5
,
p
p
.
254
~
261
I
SS
N:
2089
-
4856
254
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ia
e
s
jo
u
r
n
a
l.c
o
m/o
n
lin
e/in
d
ex
.
p
h
p
/I
J
RA
Rev
iew
of Visio
n
-
Ba
sed Ro
bo
t
Na
v
ig
a
tion
M
ethod
B
ud
i R
a
h
m
a
ni
*
,
A.
E
.
P
utr
a
**
,
A.
H
a
rj
o
k
o
**
,
T
.
K
.
P
riy
a
m
bo
do
**
*
De
p
a
rtm
e
n
t
o
f
In
f
o
r
m
a
ti
c
s
,
S
TM
IK Ban
jarb
a
ru
,
In
d
o
n
e
sia
**
F
a
c
u
lt
y
o
f
M
a
th
e
m
a
ti
c
a
n
d
S
c
ien
c
e
,
G
a
d
jah
M
a
d
a
Un
iv
e
rsity
,
In
d
o
n
e
sia
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
J
u
l
12
,
2
0
1
5
R
ev
i
s
ed
Oct
2
4
,
2
0
1
5
A
cc
ep
ted
No
v
11
,
2
0
1
5
V
isio
n
-
b
a
se
d
ro
b
o
t
n
a
v
ig
a
ti
o
n
i
s
a
re
se
a
rc
h
th
e
m
e
th
a
t
c
o
n
ti
n
u
e
s
to
b
e
d
e
v
e
lo
p
e
d
u
p
to
n
o
w
b
y
th
e
re
s
e
a
rc
h
e
rs
in
th
e
f
ield
o
f
ro
b
o
ti
c
s.
T
h
e
re
a
r
e
in
n
u
m
e
ra
b
le
m
e
th
o
d
s
o
r
a
lg
o
rit
h
m
s
a
re
d
e
v
e
lo
p
e
d
,
a
n
d
t
h
is
p
a
p
e
r
d
e
sc
rib
e
d
th
e
re
v
iew
s
o
f
th
e
m
e
th
o
d
s.
T
h
e
m
e
th
o
d
s
a
re
d
isti
n
g
u
ish
e
d
w
h
e
th
e
r
th
e
r
o
b
o
t
is
e
q
u
ip
p
e
d
w
it
h
th
e
n
a
v
ig
a
ti
o
n
m
a
p
(
m
a
p
-
b
a
se
d
),
th
e
m
a
p
is
b
u
il
t
in
c
re
m
e
n
tally
a
s
ro
b
o
t
o
b
se
rv
e
s
t
h
e
e
n
v
iro
n
m
e
n
t
(m
a
p
-
b
u
il
d
in
g
),
o
r
th
e
ro
b
o
t
n
a
v
ig
a
tes
u
sin
g
n
o
m
a
p
(
m
a
p
les
s).
In
th
is
p
a
p
e
r
w
il
l
d
e
sc
rib
e
d
n
a
v
ig
a
ti
o
n
m
e
th
o
d
s
o
f
m
a
p
-
b
a
se
d
,
m
a
p
-
b
u
il
d
in
g
,
a
n
d
m
a
p
les
s ca
te
g
o
ry
.
K
ey
w
o
r
d
:
Map
-
B
ased
Map
-
B
u
ild
i
n
g
Ma
p
less
Nav
i
g
atio
n
Vis
io
n
-
B
ased
Co
p
y
rig
h
t
©
2
0
1
5
In
stit
u
te o
f
A
d
v
a
n
c
e
d
E
n
g
i
n
e
e
rin
g
a
n
d
S
c
ien
c
e
.
Al
l
rig
h
ts
re
se
rv
e
d
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
B
u
d
i Rah
m
a
n
i
Dep
ar
t
m
en
t o
f
I
n
f
o
r
m
atic
s
,
ST
MI
K
B
an
j
a
r
b
ar
u
,
I
n
d
o
n
esia
.
E
-
m
a
il:
b
u
d
ir
ah
m
a
n
i
@
g
m
ai
l.c
o
m
1.
I
NT
RO
D
UCT
I
O
N
Nav
i
g
atio
n
ca
n
b
e
d
ef
i
n
ed
as
a
p
r
o
ce
s
s
to
d
eter
m
in
e
a
s
u
it
ab
le
an
d
s
a
f
e
p
at
h
b
et
w
ee
n
t
h
e
s
tar
tin
g
p
o
in
t
an
d
th
e
d
esti
n
atio
n
p
o
in
t
w
h
er
e
th
e
r
o
b
o
t
m
o
v
e
s
t
h
e
m
[
1
]
.
Nex
t
n
av
ig
at
io
n
o
n
a
m
o
b
ile
r
o
b
o
t
ca
n
also
b
e
d
ef
in
ed
as
th
e
ab
ilit
y
to
m
o
v
e
in
a
n
y
p
ar
tic
u
lar
en
v
ir
o
n
m
en
t,
o
r
s
cien
ce
i
n
g
u
id
in
g
a
m
o
b
ile
r
o
b
o
t
th
at
ca
n
m
o
v
e
o
n
t
h
e
en
v
ir
o
n
m
en
t
[
2
]
.
A
s
f
o
r
th
e
p
r
o
b
lem
s
t
h
at
a
cc
o
m
p
a
n
y
t
h
i
s
p
r
o
ce
s
s
is
th
e
n
av
i
g
atio
n
ca
n
b
e
d
ef
in
ed
i
n
t
h
r
ee
q
u
e
s
tio
n
s
,
n
a
m
el
y
:
"
W
h
er
e
a
m
I
"
,
"
W
h
er
e
a
m
I
g
o
i
n
g
"
,
an
d
"
Ho
w
d
o
I
g
et
th
er
e"
.
Fo
r
th
e
f
ir
s
t
a
n
d
s
ec
o
n
d
q
u
esti
o
n
s
ca
n
b
e
an
s
w
er
ed
b
y
co
m
p
letin
g
t
h
e
ap
p
r
o
p
r
iate
r
o
b
o
t
w
it
h
s
e
n
s
o
r
s
,
w
h
ile
t
h
e
th
ir
d
q
u
esti
o
n
ca
n
b
e
d
o
n
e
w
it
h
an
ef
f
ec
tiv
e
p
la
n
n
in
g
s
y
s
te
m
n
a
v
ig
a
tio
n
.
T
h
e
n
a
v
i
g
atio
n
s
y
s
t
e
m
it
s
elf
is
d
ir
ec
tl
y
r
elate
d
to
th
e
p
r
esen
ce
o
f
th
e
s
en
s
o
r
s
u
s
ed
in
r
o
b
o
ts
an
d
t
h
e
s
tr
u
ct
u
r
e
o
f
th
e
en
v
ir
o
n
m
e
n
t,
an
d
th
at
m
ea
n
s
th
er
e
w
ill
a
l
w
a
y
s
m
atc
h
th
e
p
u
r
p
o
s
e
b
u
ilt
r
o
b
o
t
an
d
th
e
e
n
v
ir
o
n
m
e
n
t
i
n
w
h
ic
h
th
e
r
o
b
o
t
w
il
l
b
e
o
p
er
ated
[
3
]
.
Vis
io
n
-
b
ased
n
av
ig
atio
n
tr
e
m
en
d
o
u
s
p
r
o
g
r
es
s
w
it
h
t
h
e
i
m
p
le
m
en
ta
tio
n
o
f
v
ar
io
u
s
a
u
to
n
o
m
o
u
s
v
e
h
icle,
w
h
et
h
er
it
is
b
ein
g
r
u
n
o
n
l
an
d
(
Au
to
n
o
m
o
u
s
Gr
o
u
n
d
V
eh
icles
/
A
GV)
,
at
s
ea
A
u
to
n
o
m
o
u
s
U
n
d
er
w
ater
Veh
icle
s
/
A
UV,
a
n
d
in
t
h
e
air
(
Un
m
an
n
ed
A
er
ial
Ve
h
icles/
U
A
V)
.
R
e
g
ar
d
les
s
o
f
t
h
e
t
y
p
e
o
f
v
eh
ic
le
o
r
r
o
b
o
t is
b
u
ilt,
t
h
en
t
h
e
s
y
s
te
m
u
t
ilize
s
a
v
i
s
io
n
s
en
s
o
r
f
o
r
n
a
v
i
g
at
io
n
p
u
r
p
o
s
es,
ca
n
r
o
u
g
h
l
y
b
e
d
iv
id
ed
in
to
t
w
o
g
en
er
al
ca
te
g
o
r
ies:
s
y
s
te
m
s
th
at
r
eq
u
ir
e
p
r
i
o
r
k
n
o
w
led
g
e
o
f
th
e
en
v
ir
o
n
m
en
t
in
w
h
ic
h
it
w
il
l
b
e
o
p
e
r
ated
(
in
th
is
ca
s
e
th
e
s
y
s
te
m
r
eq
u
ir
es
m
ap
s
/
f
o
ld
er
)
an
d
s
y
s
te
m
s
wh
o
s
ee
e
n
v
ir
o
n
m
e
n
tal
co
n
d
it
io
n
s
to
w
h
ich
h
e
w
il
l
n
av
i
g
ate.
S
y
s
te
m
s
th
at
r
eq
u
ir
e
a
m
ap
ca
n
b
e
s
u
b
d
iv
id
ed
i
n
to
f
o
ld
er
s
-
u
s
i
n
g
s
y
s
te
m
s
a
n
d
to
p
o
lo
g
ical
m
ap
-
b
ased
s
y
s
te
m
s
[
1
]
.
As
th
e
n
a
m
e
s
u
g
g
es
ts
,
th
e
n
t
h
e
n
a
v
ig
a
tio
n
s
y
s
te
m
u
s
i
n
g
a
m
ap
(
m
a
p
-
u
s
in
g
n
a
v
i
g
atio
n
s
y
s
te
m
s
)
s
h
o
u
ld
in
cl
u
d
e
a
co
m
p
lete
m
ap
o
f
th
e
e
n
v
ir
o
n
m
en
t
b
ef
o
r
e
s
tar
tin
g
n
a
v
i
g
atio
n
.
W
h
ile
th
e
m
etr
i
c
m
ap
-
b
u
ild
in
g
s
y
s
te
m
s
all
o
v
e
r
th
e
m
ap
it
s
el
f
b
u
il
t
a
n
d
u
s
e
d
in
t
h
e
n
ex
t
p
h
a
s
e
o
f
n
a
v
i
g
a
t
io
n
.
F
u
r
th
er
m
o
r
e,
o
th
er
s
y
s
te
m
s
th
at
ar
e
in
th
is
ca
teg
o
r
y
is
a
s
y
s
te
m
th
at
ca
n
p
er
f
o
r
m
s
el
f
-
lo
ca
lize
o
n
th
e
en
v
ir
o
n
m
e
n
t
s
i
m
u
lta
n
eo
u
s
l
y
p
er
f
o
r
m
ed
d
u
r
in
g
m
ap
co
n
s
tr
u
ctio
n
p
u
r
p
o
s
es
[
4
]
.
A
n
d
o
th
er
t
y
p
es
o
f
m
ap
-
b
u
ild
in
g
n
a
v
i
g
atio
n
s
y
s
te
m
s
ar
e
en
co
u
n
ter
ed
eg
al:
v
is
u
al
s
o
n
ar
-
b
a
s
ed
s
y
s
te
m
s
o
r
lo
ca
l
f
o
ld
er
-
b
ased
s
y
s
te
m
s
.
B
o
th
o
f
th
e
s
e
s
y
s
te
m
s
co
llect
e
n
v
ir
o
n
m
e
n
tal
d
ata
w
h
en
n
a
v
ig
at
in
g
,
an
d
b
u
ild
a
lo
ca
l
f
o
ld
er
th
at
is
u
s
ed
t
o
s
u
p
p
o
r
t
in
o
r
d
er
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
RA
I
SS
N:
2089
-
4856
R
ev
iew
o
f V
is
io
n
-
B
a
s
ed
R
o
b
o
t
N
a
vig
a
tio
n
Meth
o
d
(
B
u
d
i R
a
h
ma
n
i)
255
to
b
e
ap
p
r
o
p
r
iate
n
av
ig
at
io
n
al
p
u
r
p
o
s
e.
A
s
f
o
r
th
e
lo
ca
l
m
a
p
in
clu
d
es
m
ap
p
in
g
th
e
b
ar
r
ier
an
d
th
e
s
p
ac
e,
an
d
th
is
is
u
s
u
all
y
a
f
u
n
c
tio
n
o
f
th
e
an
g
le
o
f
v
ie
w
o
f
th
e
ca
m
er
a
[
1
]
.
T
h
e
last
s
y
s
te
m
,
n
a
m
el
y
:
a
to
p
o
lo
g
ical
m
ap
-
b
ased
,
w
h
ich
b
u
ild
s
a
to
p
o
lo
g
y
m
ap
t
h
at
co
n
s
is
t
s
o
f
n
o
d
es
(
n
o
d
es)
ar
e
co
n
n
ec
ted
b
y
a
li
n
e
,
w
h
er
e
th
e
v
er
tices
r
ep
r
esen
t
th
e
p
lace
/
s
p
ec
i
f
ic
p
o
s
itio
n
s
o
n
th
e
en
v
ir
o
n
m
e
n
t,
an
d
li
n
k
s
r
ep
r
esen
t
th
e
d
i
s
ta
n
ce
o
r
tr
av
el
t
i
m
e
b
et
w
ee
n
t
h
e
t
w
o
v
er
tices
[
1
]
[
5
]
.
T
h
e
n
e
x
t
Nav
ig
at
io
n
S
y
s
t
e
m
i
s
m
ap
les
s
n
a
v
i
g
atio
n
s
y
s
t
e
m
s
w
h
ich
m
o
s
tl
y
in
cl
u
d
es
r
ea
ctiv
e
tec
h
n
iq
u
e
t
h
at
u
s
es
v
is
u
al
c
u
es
ar
e
b
u
i
lt
f
r
o
m
i
m
ag
e
s
e
g
m
e
n
tatio
n
,
o
p
tical
f
lo
w
,
o
r
th
e
s
ea
r
ch
p
r
o
ce
s
s
f
ea
t
u
r
es
b
et
w
e
en
i
m
a
g
e
f
r
a
m
e
s
o
b
tain
ed
.
T
h
er
e
is
n
o
r
ep
r
ese
n
tatio
n
o
f
t
h
e
e
n
v
ir
o
n
m
e
n
t
o
n
th
ese
s
y
s
te
m
s
,
an
d
e
n
v
ir
o
n
m
en
ts
s
ee
n
/
p
er
ce
iv
ed
to
n
a
v
ig
ate
t
h
e
s
y
s
te
m
,
r
ec
o
g
n
ize
o
b
j
ec
ts
,
o
r
b
r
o
w
s
e
lan
d
m
ar
k
[
4
]
.
I
n
ad
d
itio
n
to
t
h
e
k
n
o
w
led
g
e
o
f
t
h
e
e
n
v
ir
o
n
m
en
t
d
escr
ib
ed
ab
o
v
e,
t
h
en
t
h
e
r
o
b
o
t
v
is
io
n
-
b
ased
n
av
i
g
atio
n
i
s
d
is
ti
n
g
u
is
h
ed
al
s
o
b
y
t
h
e
e
n
v
ir
o
n
m
e
n
t
in
w
h
ich
t
h
e
r
o
b
o
t
is
o
p
er
ated
as
f
o
llo
w
s
:
i
n
d
o
o
r
an
d
o
u
td
o
o
r
.
B
o
th
t
y
p
es
ar
e
al
s
o
s
u
r
r
o
u
n
d
i
n
g
en
v
ir
o
n
m
e
n
t
o
r
n
a
v
ig
a
tio
n
m
o
d
el
t
h
at
co
n
s
i
s
ts
o
f
m
ap
-
u
s
in
g
/
m
ap
-
b
ased
,
f
o
ld
er
-
b
u
ild
in
g
,
an
d
m
a
p
less
n
a
v
i
g
atio
n
s
y
s
te
m
.
2.
T
H
E
VI
SI
O
N
-
B
AS
E
D
NAV
I
G
A
T
I
O
N
Vis
io
n
-
b
ased
n
a
v
i
g
atio
n
m
e
th
o
d
ca
n
b
e
ca
teg
o
r
ized
as
m
a
p
-
b
ased
n
a
v
ig
at
io
n
,
m
ap
-
b
u
il
d
in
g
b
ased
n
av
i
g
atio
n
,
an
d
m
ap
le
s
s
n
av
i
g
atio
n
.
2
.
1
.
M
a
p
-
B
a
s
ed
Na
v
ig
a
t
io
n
I
n
th
e
m
ap
-
b
ased
n
a
v
i
g
atio
n
o
r
m
ap
-
u
s
i
n
g
it
s
ee
m
s
c
lear
th
at
f
o
r
th
e
p
u
r
p
o
s
es
o
f
n
a
v
i
g
atio
n
,
th
e
r
o
b
o
t
is
eq
u
ip
p
e
d
w
i
th
a
m
ap
o
f
th
e
en
v
ir
o
n
m
e
n
t
in
w
h
ic
h
it
w
ill
b
e
o
p
er
ated
[
6
]
.
T
h
er
e
a
r
e
s
ev
er
al
m
o
d
els
o
f
m
ap
s
u
s
ed
,
i
n
cl
u
d
in
g
:
g
eo
m
et
r
ic
m
o
d
els,
to
p
o
lo
g
ic
al,
s
eq
u
e
n
ce
o
f
i
m
a
g
e
[
4
]
.
On
e
o
f
m
a
p
-
b
ased
n
a
v
i
g
atio
n
i
m
p
le
m
en
ta
tio
n
as
in
[
7
]
w
h
ic
h
u
s
e
s
v
i
s
u
al
-
b
ased
n
a
v
i
g
atio
n
s
y
s
te
m
w
it
h
s
ter
eo
ca
m
er
a
o
n
a
w
h
ee
led
r
o
b
o
t
g
o
lf
b
all
s
’
co
llecto
r
.
I
t’
s
ai
d
ed
b
y
t
h
e
w
id
e
a
n
g
le
ca
m
er
a
m
o
u
n
ted
o
n
to
p
o
f
t
h
e
g
o
lf
co
u
r
s
e
w
i
t
h
s
p
ec
if
icatio
n
:
-
C
o
v
er
ag
e
ar
ea
is
o
f
2
0
m
x
2
0
m
-
Ver
tical
v
i
e
w
i
n
g
an
g
le
i
s
8
0
o
an
d
h
o
r
izo
n
tal
v
ie
w
i
n
g
a
n
g
le
is
5
5
o
-
T
h
e
h
ei
g
h
t
o
f
t
h
e
ca
m
er
a
i
n
s
ta
llatio
n
is
7
m
ab
o
v
e
th
e
g
r
o
u
n
d
-
T
h
e
m
a
x
i
m
u
m
r
eso
l
u
tio
n
o
f
t
h
is
ca
m
er
a
is
eq
u
al
to
1
2
8
0
x
7
8
0
p
ix
els.
T
h
e
w
a
y
o
f
t
h
e
s
y
s
te
m
w
o
r
k
s
is
s
tar
ted
b
y
t
h
e
ca
m
er
a
ca
tch
es
th
e
i
m
a
g
e
an
d
t
h
en
p
r
o
ce
s
s
ed
b
y
a
co
m
p
u
ter
s
er
v
er
w
h
ich
t
h
en
b
u
ild
s
n
av
i
g
atio
n
m
ap
g
r
id
-
s
h
a
p
ed
,
o
r
it
d
ef
i
n
ed
as
o
cc
u
p
an
c
y
g
r
id
m
ap
[
8
]
[
9
]
.
T
h
is
o
cc
u
p
an
c
y
g
r
id
m
ap
ca
n
i
n
d
icate
w
h
er
e
to
p
o
s
itio
n
o
f
th
e
r
o
b
o
t
o
n
th
e
g
o
lf
co
u
r
s
e,
an
d
w
h
er
ei
n
t
h
e
p
o
s
iti
o
n
o
f
th
e
b
alls
to
b
e
ta
k
e
n
.
A
c
co
r
d
in
g
to
t
h
e
m
ap
d
eter
m
i
n
e
d
b
y
th
e
s
er
v
er
,
th
e
r
o
b
o
t
ca
n
m
o
v
e
to
w
ar
d
a
ce
r
tain
p
o
s
itio
n
,
b
ased
o
n
t
h
e
in
f
o
r
m
atio
n
s
en
t
w
ir
eles
s
l
y
[
1
0
]
[
1
1
]
[
1
2
]
[
1
3
]
.
I
n
th
i
s
ca
teg
o
r
y
t
h
er
e
i
s
al
s
o
a
m
ap
-
b
ased
n
a
v
i
g
atio
n
ap
p
r
o
ac
h
es
u
s
in
g
s
e
m
a
n
tic
-
b
ased
m
ap
.
T
h
is
ap
p
r
o
ac
h
is
ca
lled
h
o
lo
g
r
ap
h
y
m
ap
is
d
iv
id
ed
in
t
o
th
r
ee
h
ier
ar
ch
ical
ite
m
s
in
t
h
e
h
o
u
s
e,
an
d
is
d
iv
id
ed
in
to
1
3
class
es
o
f
o
b
j
ec
ts
[
1
3
]
.
2
.
2
.
M
a
p B
uil
din
g
Na
v
ig
a
t
io
n
2
.
2
.
1
.
M
et
ric
M
a
p
R
o
b
o
t
n
av
i
g
atio
n
u
s
i
n
g
m
etr
i
c
-
m
ap
ap
p
r
o
ac
h
in
th
e
ca
teg
o
r
y
m
ap
-
b
u
ild
in
g
co
m
m
o
n
l
y
r
ef
er
r
ed
to
also
as
g
r
id
-
b
ased
m
ap
,
i
n
ad
d
itio
n
to
o
th
er
m
o
d
el
s
,
n
a
m
el
y
:
to
p
o
lo
g
ical
m
ap
,
h
y
b
r
id
m
ap
.
I
n
th
e
s
tu
d
y
[
1
4
]
th
e
p
r
ev
io
u
s
m
ap
w
a
s
b
u
i
lt
b
y
a
lo
ca
l
m
ap
p
in
g
to
s
t
u
d
y
t
h
e
m
ap
g
r
id
an
d
f
ea
t
u
r
es
t
h
e
i
m
ag
e
o
f
a
p
lace
t
h
at
cr
a
w
led
lik
e
a
co
r
n
er
r
o
o
m
an
d
s
o
o
n
.
T
h
en
in
ea
ch
o
f
th
ese
p
lace
s
ar
e
cr
ea
ted
b
y
u
s
in
g
a
g
r
id
m
ap
Fas
tS
L
A
M
[
8
]
[
1
5
]
[
1
6
]
,
w
h
i
ch
d
is
t
in
g
u
is
h
i
m
a
g
e
f
ea
t
u
r
es
av
ailab
le
in
ea
c
h
p
lace
w
it
h
i
m
a
g
e
f
ea
tu
r
e
s
t
h
at
h
av
e
b
ee
n
s
to
r
ed
in
t
h
e
d
atab
ase
[
1
4
]
.
Nex
t
at
th
ese
lo
ca
tio
n
s
,
w
it
h
a
s
i
m
p
ler
f
o
r
m
b
et
w
e
en
p
lace
s
,
th
e
n
t
h
e
m
ap
d
etail
i
s
n
o
t
m
ad
e,
b
u
t
t
h
e
co
n
n
ec
tio
n
s
b
et
w
ee
n
t
h
e
i
n
f
o
r
m
atio
n
o
n
l
y
w
it
h
in
tr
icate
s
h
ap
es
ar
e
s
t
u
d
ied
.
C
o
n
n
ec
tio
n
to
p
o
lo
g
y
is
b
a
s
ica
ll
y
a
p
r
o
ce
s
s
w
h
ic
h
s
ee
n
w
h
et
h
er
it
i
s
a
n
e
w
p
lace
o
r
a
p
lace
h
as
b
ee
n
v
is
ited
b
y
t
h
e
r
o
b
o
t.
T
h
e
d
ec
is
io
n
o
b
tain
ed
b
y
u
s
i
n
g
i
m
a
g
e
f
ea
t
u
r
e
s
m
atc
h
in
g
p
r
o
ce
s
s
b
y
u
s
i
n
g
s
p
ee
d
ed
Up
R
o
b
u
s
t
Featu
r
es (
SU
R
F)
[
1
4
]
.
2
.
2
.
2
.
Sco
re
M
a
p B
uil
din
g
I
n
t
h
is
s
ec
tio
n
,
o
n
e
o
f
t
h
e
n
av
ig
a
tio
n
m
et
h
o
d
s
d
ev
e
lo
p
ed
b
y
ca
te
g
o
r
y
m
ap
b
u
i
ld
in
g
t
h
at
s
co
r
es
n
av
i
g
atio
n
m
ap
.
I
t
is
a
n
o
v
el
alg
o
r
ith
m
t
h
at
w
as
d
e
v
elo
p
ed
f
r
o
m
i
n
f
o
r
m
atio
n
d
er
iv
ed
f
r
o
m
t
h
e
s
ter
eo
ca
m
er
a
[
1
7
]
.
T
h
e
aim
is
to
esti
m
ate
t
h
e
f
r
ee
s
p
ac
e
o
f
th
e
v
e
h
i
cle
(
ca
r
)
w
h
ic
h
is
in
f
r
o
n
t
o
f
w
h
er
e
th
e
s
y
s
te
m
i
s
r
u
n
,
p
ar
ticu
lar
l
y
f
o
r
n
a
v
ig
at
io
n
o
n
th
e
h
i
g
h
w
a
y
.
B
y
u
til
izin
g
th
e
d
if
f
er
e
n
ce
m
ap
(
d
is
p
ar
it
y
m
ap
)
[
1
8
]
,
it
w
i
ll o
b
tai
n
in
f
o
r
m
atio
n
o
n
w
h
et
h
er
th
e
c
o
n
d
itio
n
o
f
th
e
v
e
h
icle
i
n
f
r
o
n
t
o
f
h
i
m
w
a
s
'
s
o
lid
'
o
r
'
r
ar
el
y
'
.
F
u
r
th
er
to
t
h
e
d
ev
elo
p
m
en
t
o
f
s
co
r
es
f
o
ld
er
,
b
ec
au
s
e
t
h
e
s
e
n
s
o
r
u
s
ed
is
a
s
t
er
eo
ca
m
er
a,
w
h
ich
is
ca
r
r
ied
o
u
t
n
e
x
t
i
s
a
s
ter
eo
m
atc
h
in
g
p
r
o
ce
s
s
b
ased
o
n
im
ag
e
d
ata
t
h
at
is
p
ass
ed
lo
n
g
it
u
d
in
al
r
o
ad
s
u
r
f
ac
e.
Dete
ct
io
n
o
f
f
r
ee
s
p
ac
e
i
s
d
o
n
e
b
y
e
x
tr
ac
ti
n
g
t
h
e
r
o
ad
s
u
r
f
ac
e
w
ith
o
u
t a
n
y
o
b
s
tacle
.
T
h
e
d
etec
tio
n
is
d
o
n
e
w
it
h
th
e
p
r
o
ce
d
u
r
e,
n
a
m
el
y
:
a)
First
u
s
e
o
f
h
i
g
h
Vli
n
e
a
n
d
co
n
s
id
er
in
g
a
u
s
ed
v
e
h
icle
(
v
eh
icle
r
esear
c
h
)
.
Ma
p
o
f
th
e
d
i
f
f
er
en
ce
(
d
is
p
ar
ity
m
ap
)
is
d
i
v
id
ed
in
t
o
t
w
o
p
ar
ts
:
th
e
o
b
s
tacle
d
i
s
p
ar
it
y
m
ap
a
n
d
th
e
r
o
ad
s
u
r
f
ac
e
d
is
p
ar
it
y
m
ap
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4856
IJ
RA
Vo
l.
4
,
No
.
4
,
Decem
b
er
2
0
1
5
:
2
5
4
–
2
6
1
256
Fo
r
Vlin
e
it
s
elf
r
ep
r
esen
t
s
t
h
e
p
r
o
f
ile
o
f
t
h
e
r
o
ad
s
u
r
f
ac
e
al
o
n
g
th
e
d
ir
ec
tio
n
o
f
v
i
s
io
n
ca
m
er
as
th
at
ar
e
esti
m
ated
u
s
i
n
g
m
e
th
o
d
s
Dij
k
s
tr
a's [
1
9
]
.
b)
Seco
n
d
,
in
ea
c
h
co
lu
m
n
o
f
t
h
e
d
is
p
ar
it
y
m
ap
,
a
d
is
p
ar
it
y
h
is
t
o
g
r
a
m
w
h
ic
h
is
a
f
r
eq
u
e
n
c
y
o
f
a
d
is
p
ar
it
y
i
n
a
r
an
g
e
[
0
,
d
m
a
x
]
is
m
ad
e.
T
h
e
m
a
x
i
m
u
m
v
a
lu
e
s
o
f
ea
ch
co
lu
m
n
o
f
th
e
h
is
to
g
r
a
m
p
o
s
s
ib
i
lit
y
,
f
o
r
m
ed
b
y
a
s
in
g
le
o
b
s
tacle
as a
n
o
b
s
tacle
u
s
u
all
y
h
a
v
e
th
e
s
a
m
e
d
i
s
p
ar
it
y
.
c)
T
h
ir
d
,
to
r
ed
u
ce
th
e
o
cc
u
r
r
en
ce
o
f
er
r
o
r
s
,
th
is
p
ap
er
in
tr
o
d
u
ce
s
a
n
e
w
co
n
ce
p
t
th
at
s
co
r
es
th
e
f
o
ld
er
th
at
r
ep
r
esen
ts
t
h
e
p
o
s
s
ib
ilit
y
o
f
t
h
e
ex
i
s
ten
ce
o
f
th
e
o
b
s
tacle
.
T
h
en
t
h
e
s
co
r
e
d
is
p
ar
it
y
m
ap
was
co
n
s
tr
u
cted
f
r
o
m
h
i
s
to
g
r
a
m
ab
o
v
e
o
b
s
ta
cle
d
is
p
ar
it
y
m
ap
a
n
d
t
h
e
r
o
ad
s
u
r
f
ac
e
d
is
p
ar
it
y
m
ap
,
th
en
b
o
th
ar
e
co
m
b
i
n
ed
.
Usi
n
g
d
y
n
a
m
ic
p
r
o
g
r
a
m
m
i
n
g
,
f
r
o
m
t
h
e
co
m
b
i
n
atio
n
o
f
th
e
t
w
o
f
o
ld
er
is
s
ea
r
ch
ed
f
o
r
a
co
r
r
esp
o
n
d
in
g
d
is
p
ar
it
y
s
ep
ar
atel
y
to
m
ar
k
o
b
s
tacle
s
o
r
b
ar
r
ier
s
ar
e
clo
s
est
to
th
e
s
ter
eo
ca
m
er
a
an
d
th
e
r
o
ad
s
u
r
f
ac
e.
d)
T
h
e
last
s
tep
i
s
to
ex
tr
ac
t
co
n
s
tr
ain
t
s
(
b
o
u
n
d
ar
y
)
b
et
w
ee
n
t
h
e
r
o
ad
s
u
r
f
ac
e
an
d
o
b
s
tacle
s
,
w
h
ic
h
i
n
t
h
is
ca
s
e
is
u
s
ed
V
li
n
e
an
d
Uli
n
e
as
ilu
s
tr
ated
in
F
ig
u
r
e
1
a
n
d
th
e
lo
w
er
p
ar
t
o
f
th
e
b
o
u
n
d
ar
y
li
n
e
(
b
o
r
d
er
lin
e)
is
a
f
r
ee
s
p
ac
e
.
Fig
u
r
e
1
.
Fre
e
s
p
ac
e
d
etec
tio
n
ilu
s
tr
atio
n
3.
P
O
T
E
N
T
I
A
L
B
AN
M
E
T
H
O
D
T
h
ese
P
o
ten
tial
B
an
m
et
h
o
d
s
m
i
m
ic
h
o
w
h
u
m
an
s
in
av
o
id
a
n
ce
w
h
e
n
it
f
i
n
d
s
w
h
e
n
w
alk
i
n
g
,
an
d
in
th
is
ca
s
e
th
e
m
a
n
w
o
u
ld
tr
y
t
o
m
o
v
e
f
r
o
m
th
e
h
itc
h
to
th
e
p
lace
o
r
p
o
s
itio
n
m
o
r
e
s
ec
u
r
e
.
T
h
is
m
eth
o
d
w
as
o
r
ig
in
all
y
d
e
v
elo
p
ed
f
r
o
m
th
e
tr
ad
itio
n
al
n
av
ig
at
io
n
m
et
h
o
d
k
n
o
w
n
a
s
ar
ti
f
icial
p
o
te
n
tia
l
f
ie
ld
m
et
h
o
d
an
d
w
a
s
f
ir
s
t
in
tr
o
d
u
ce
d
i
n
1
9
8
6
b
y
Dr
.
K
h
atib
[
2
0
]
.
T
h
is
m
et
h
o
d
w
a
s
o
r
ig
in
al
l
y
u
s
ed
as
a
m
et
h
o
d
to
av
o
id
t
h
e
o
b
s
tacle
,
an
d
p
ath
p
lan
n
in
g
,
th
e
r
o
b
o
t
m
a
n
ip
u
lato
r
.
T
h
e
g
en
e
r
al
id
ea
is
to
cr
ea
te
a
v
ir
tu
al,
p
o
ten
tia
l
f
o
r
ce
f
ield
o
n
an
o
b
j
ec
t
th
at
is
'
s
ee
n
'
b
y
th
e
ca
m
er
a,
f
r
o
m
w
h
ic
h
w
ill
r
etu
r
n
v
ir
t
u
all
y
d
eter
m
i
n
ed
th
e
f
ield
ar
o
u
n
d
th
e
o
b
j
ec
t
th
at
ca
n
b
e
p
ass
ed
s
af
el
y
in
o
r
d
er
to
n
av
ig
a
te
th
e
r
o
b
o
t
[
2
1
]
.
L
ater
in
th
e
p
r
o
g
r
ess
io
n
to
p
o
ten
tial
b
an
m
et
h
o
d
,
at
ev
er
y
iter
a
tio
n
s
te
p
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t
to
d
etec
t
th
e
p
o
s
s
ib
ilit
y
o
f
a
co
ll
is
io
n
.
I
f
t
h
er
e
is
a
p
o
s
s
ib
ilit
y
o
f
a
co
lli
s
io
n
,
th
e
n
th
e
p
o
ten
tial
tire
d
escr
ib
ed
o
n
a
g
r
id
m
ap
.
B
asicall
y
p
o
ten
tial
tire
is
th
e
v
alu
e
o
f
co
n
f
id
en
ce
b
y
a
r
o
b
o
t
w
h
er
e
h
e
h
ad
to
m
a
n
eu
v
er
ag
a
in
s
t
a
m
o
v
i
n
g
o
b
s
tacle
.
Vir
t
u
al
ce
r
tain
t
y
d
is
tr
ib
u
t
io
n
o
f
v
al
u
es
ar
o
u
n
d
t
h
e
co
llis
io
n
p
o
in
t
is
s
h
o
w
n
i
n
Fi
g
u
r
e
1
.
T
h
e
v
a
lu
e
o
f
t
h
e
v
ir
t
u
al
ce
r
tai
n
t
y
t
h
is
w
ill
te
n
d
to
in
cr
ea
s
e
i
n
t
h
e
d
ir
ec
tio
n
o
f
m
o
v
e
m
e
n
t
o
f
t
h
e
b
ar
r
ier
s
,
th
a
t
v
alu
e
is
th
e
p
r
ed
ictio
n
o
f
th
e
p
o
s
itio
n
o
f
th
e
h
i
tch
p
er
2
m
s
tep
s
b
e
f
o
r
e
an
d
af
ter
t
h
e
co
llis
io
n
,
an
d
is
ca
lc
u
lated
b
y
t
h
e
f
o
llo
w
in
g
eq
u
atio
n
: [
2
0
]
[
2
2
]
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
RA
I
SS
N:
2089
-
4856
R
ev
iew
o
f V
is
io
n
-
B
a
s
ed
R
o
b
o
t
N
a
vig
a
tio
n
Meth
o
d
(
B
u
d
i R
a
h
ma
n
i)
257
(
)
W
h
er
e:
VC
=
Vir
tu
al
C
er
tai
n
t
y
C
m
a
x
=
m
ax
i
m
u
m
v
al
u
e
C
er
tain
t
y
k
=
co
n
s
tan
t
m
=
m
ax
i
m
u
m
v
al
u
e
p
r
ed
ictio
n
s
tep
Fig
u
r
e
2
.
P
o
ten
tial B
an
tr
an
s
m
itted
th
r
o
u
g
h
t
h
e
g
r
id
m
ap
[
2
2
]
4.
ST
E
RE
O
-
B
AS
E
D
VI
SUA
L
NAVI
G
A
T
I
O
N
Fro
m
t
h
e
n
a
m
e
o
b
v
io
u
s
l
y
r
o
b
o
t
n
av
i
g
atio
n
m
e
th
o
d
r
elies
o
n
th
e
s
ter
eo
ca
m
er
a
is
u
s
ed
.
I
n
th
e
ex
a
m
p
le
i
m
p
le
m
e
n
tatio
n
o
f
t
h
is
m
et
h
o
d
,
th
e
n
a
v
i
g
atio
n
is
d
o
n
e
is
o
u
t
s
id
e
t
h
e
r
o
o
m
a
u
to
m
atica
ll
y
b
y
w
h
ee
led
r
o
b
o
t
o
n
a
p
r
ev
io
u
s
l
y
u
n
k
n
o
w
n
e
n
v
ir
o
n
m
e
n
t,
u
s
i
n
g
s
ter
eo
c
a
m
er
as
a
n
d
r
o
b
o
ts
ar
e
n
o
n
h
o
lo
n
o
m
ic
m
o
d
els.
T
h
e
f
ir
s
t
s
tep
i
s
ca
r
r
ied
o
u
t
f
o
r
th
e
e
x
p
lo
r
atio
n
o
f
t
h
e
u
n
k
n
o
w
n
e
n
v
ir
o
n
m
en
t
is
c
o
n
s
tr
u
ct
io
n
o
n
th
e
s
u
r
r
o
u
n
d
in
g
en
v
ir
o
n
m
e
n
t i
n
r
e
al
-
ti
m
e
[
2
3
]
.
T
h
en
f
r
o
m
t
h
e
d
i
s
p
ar
it
y
i
m
a
g
e
o
b
tain
ed
f
r
o
m
a
s
ter
eo
ca
m
er
a,
an
d
th
e
d
ata
i
s
tr
a
n
s
lated
in
to
a
3
D
-
Sp
ac
e,
t
h
e
n
co
n
s
tr
u
cted
p
o
in
t
clo
u
d
m
o
d
els
f
r
o
m
t
h
e
e
n
v
ir
o
n
m
en
t
ar
o
u
n
d
th
e
m
.
T
h
e
n
e
x
t
s
tep
i
s
p
r
o
j
ec
ti
n
g
th
e
s
e
p
o
in
t
s
to
th
e
f
ield
X
Z
lo
ca
l
f
o
ld
er
an
d
p
u
t
to
g
et
h
er
i
n
ac
co
r
d
an
ce
w
it
h
th
e
v
is
u
al
o
d
o
m
e
tr
y
o
b
tai
n
ed
f
r
o
m
s
ter
eo
ca
m
er
a.
T
h
u
s
th
e
g
lo
b
al
m
ap
o
f
th
e
en
v
ir
o
n
m
e
n
t
ca
n
b
e
co
n
s
tr
u
cte
d
in
r
ea
l
-
ti
m
e.
I
n
t
h
is
s
t
u
d
y
,
t
h
e
A
*
al
g
o
r
ith
m
i
s
u
s
ed
to
in
v
esti
g
ate
o
p
ti
m
al
p
ath
[
3
]
,
an
d
n
o
n
-
lin
ea
r
b
ac
k
-
s
tep
p
in
g
co
n
tr
o
ller
g
u
id
es th
e
r
o
b
o
t to
b
e
ab
le
t
o
f
o
llo
w
th
e
p
ath
id
en
ti
f
ied
[
2
3
]
.
5.
SUB
-
G
O
AL
M
E
T
H
O
D
I
n
th
i
s
m
e
th
o
d
,
th
e
m
ap
is
b
u
ilt
b
ased
o
n
t
h
e
en
v
ir
o
n
m
e
n
tal
i
m
a
g
e
i
n
f
o
r
m
atio
n
o
b
tain
ed
f
r
o
m
a
ca
m
er
a
m
o
u
n
ted
o
n
t
h
e
r
o
b
o
t.
Fro
m
t
h
e
i
n
f
o
r
m
atio
n
t
h
at
w
as
t
h
e
n
b
u
ilt
t
h
e
b
est
i
n
f
o
r
m
atio
n
ab
o
u
t
t
h
e
n
av
i
g
atio
n
al
p
ath
s
th
at
ca
n
b
e
tak
en
b
y
t
h
e
r
o
b
o
t
s
af
el
y
.
T
h
e
f
lo
w
c
h
ar
t
o
f
t
h
is
m
et
h
o
d
is
s
h
o
w
n
i
n
Fi
g
u
r
e
4
[
3
]
.
Fig
u
r
e
3
.
Flo
w
c
h
ar
t
m
eth
o
d
o
f
n
av
ig
at
io
n
w
i
th
s
u
b
-
g
o
al
[
3
]
On
i
m
p
le
m
e
n
tatio
n
,
t
h
i
s
m
e
th
o
d
u
s
es
t
w
o
s
en
s
o
r
s
,
n
a
m
el
y
s
e
n
s
o
r
s
an
d
c
a
m
er
as
i
n
f
r
ar
ed
s
en
s
o
r
s
.
T
h
er
ef
o
r
e
th
i
s
m
et
h
o
d
d
iv
id
es
i
n
to
t
w
o
la
y
er
s
f
o
r
th
e
s
y
s
te
m
b
u
ilt.
A
t
t
h
e
b
eg
i
n
n
i
n
g
o
f
t
h
e
m
et
h
o
d
,
th
e
n
a
v
i
g
ati
o
n
d
esti
n
at
io
n
in
f
o
r
m
a
tio
n
o
b
tain
ed
ac
co
r
d
in
g
to
w
h
at
is
p
r
o
g
r
a
m
m
ed
to
t
h
e
f
i
r
s
t
la
y
er
i
n
t
h
is
m
eth
o
d
.
O
n
t
h
is
f
ir
s
t
la
y
er
i
m
a
g
e
d
ata
p
r
o
ce
s
s
i
s
co
n
ti
n
u
o
u
s
l
y
o
b
tain
ed
f
r
o
m
a
s
i
n
g
le
ca
m
er
a
is
u
s
ed
,
a
n
d
t
h
e
v
id
eo
is
th
e
n
p
r
o
ce
s
s
ed
in
a
w
a
y
s
u
c
h
as
:
-
L
o
w
p
a
s
s
f
il
ter
to
r
ed
u
ce
n
o
is
e
in
i
m
ag
e
s
ac
q
u
ir
ed
-
Dete
ct
ed
g
es
c
h
ar
ac
t
er
ize
th
e
C
a
n
n
y
ed
g
e
d
etec
t
io
n
m
eth
o
d
-
T
h
e
s
tr
en
g
th
e
n
i
n
g
o
f
t
h
e
ed
g
e
c
h
ar
ac
ter
is
tics
o
b
tain
ed
p
r
ev
io
u
s
l
y
,
i
n
o
r
d
er
to
r
ein
f
o
r
ce
th
e
i
m
a
g
e
o
b
tain
ed
-
P
er
f
o
r
m
t
h
e
o
p
er
atio
n
r
eg
io
n
g
r
o
w
i
n
g
at
th
e
ed
g
e
o
f
th
e
ch
ar
ac
ter
is
tic
i
m
a
g
e
o
f
t
h
e
o
b
j
ec
t
th
at
h
as
b
ee
n
p
r
ev
io
u
s
l
y
b
o
ld
-
C
o
n
d
u
cti
n
g
r
eg
io
n
g
r
o
w
i
n
g
o
p
er
atio
n
in
th
e
i
m
ag
e
p
ar
t
o
f
t
h
e
f
lo
o
r
-
Nex
t
i
s
to
b
u
ild
a
tr
ap
e
zo
id
al
f
lo
o
r
r
eg
io
n
s
o
cl
ea
r
l
y
t
h
e
d
i
f
f
er
e
n
ce
b
et
w
ee
n
th
e
f
lo
o
r
an
d
th
e
h
i
tch
.
Ne
x
t
w
i
th
th
e
h
e
lp
o
f
s
o
f
t
w
ar
e,
m
ap
s
o
n
th
e
e
n
v
ir
o
n
m
en
t f
r
o
m
a
p
r
ev
io
u
s
l
y
cr
ea
te
d
im
a
g
e
p
r
o
ce
s
s
i
n
g
[
2
4
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4856
IJ
RA
Vo
l.
4
,
No
.
4
,
Decem
b
er
2
0
1
5
:
2
5
4
–
2
6
1
258
I
n
Fi
g
u
r
e
3
b
elo
w
s
h
o
w
s
h
o
w
th
e
s
h
o
r
tes
t
p
ath
b
u
ilt
f
o
r
n
av
i
g
atio
n
p
u
r
p
o
s
es
r
o
b
o
t,
b
u
ilt
u
s
i
n
g
th
e
s
teep
est
d
escen
t
m
eth
o
d
[
2
5
]
.
Fig
u
r
e
3
.
Flo
w
c
h
ar
t o
f
n
a
v
i
g
a
tio
n
m
et
h
o
d
u
s
in
g
s
u
b
-
g
o
al
[
3
]
On
ce
t
h
e
n
a
v
i
g
atio
n
m
ap
o
b
tain
ed
t
h
en
t
h
e
n
ex
t
r
o
b
o
t
to
n
av
i
g
ate
b
ased
o
n
t
h
e
i
n
f
o
r
m
atio
n
a
n
d
cir
cu
m
s
ta
n
ce
s
w
h
ich
u
s
ed
in
f
r
ar
ed
s
en
s
o
r
s
to
th
e
p
o
in
t
g
o
al
b
y
ta
k
i
n
g
t
h
e
f
ir
s
t
s
u
b
-
g
o
al
p
r
ed
eter
m
in
e
d
b
y
th
e
s
y
s
te
m
.
I
f
th
e
p
u
r
p
o
s
e
/g
o
al
is
r
ea
ch
ed
th
en
t
h
e
r
o
b
o
t
w
ill
s
to
p
m
o
v
in
g
[
3
]
.
6.
M
AP
L
E
SS
NAVI
G
A
T
I
O
N
6
.
1
.
O
ptic
a
l f
lo
w
-
ba
s
ed
t
ec
hn
iqu
es
Op
ticalf
lo
w
b
ased
m
et
h
o
d
s
m
i
m
ics
h
o
w
th
e
v
is
u
al
b
eh
a
v
io
r
o
f
an
i
m
al
s
b
ee
s
,
in
w
h
ic
h
t
h
e
r
o
b
o
t
m
o
v
e
m
e
n
t
s
p
ee
d
i
s
d
eter
m
i
n
e
d
b
y
th
e
b
a
s
ic
d
i
f
f
er
e
n
ce
b
et
w
ee
n
t
h
e
i
m
a
g
e
s
ee
n
b
y
t
h
e
e
y
e
(
ca
m
er
a)
a
n
d
t
h
e
r
ig
h
t
o
f
t
h
e
i
m
a
g
e
s
ee
n
b
y
th
e
e
y
e
(
ca
m
er
a)
le
f
t,
a
n
d
th
e
r
o
b
o
t
w
ill
m
o
v
e
to
th
e
s
id
e
o
f
th
e
s
p
ee
d
i
m
a
g
e
i
s
s
m
al
ler
ch
a
n
g
e
s
[
4
]
.
T
h
is
m
et
h
o
d
is
w
id
el
y
u
s
ed
to
d
etec
t
a
n
o
b
s
tacle
,
a
n
d
f
o
llo
w
i
n
g
t
h
is
m
et
h
o
d
d
ev
elo
p
ed
f
u
r
t
h
er
i
n
m
a
n
y
alg
o
r
it
h
m
s
,
in
cl
u
d
in
g
th
e
Ho
m
-
Se
h
u
n
e
k
al
g
o
r
ith
m
(
H
S
al
g
o
r
ith
m
)
an
d
L
u
ea
s
-
Kan
ad
e
alg
o
r
ith
m
(
L
K
al
g
o
r
it
h
m
)
.
I
n
th
e
HS
al
g
o
r
ith
m
,
p
r
o
p
o
s
ed
a
n
eq
u
atio
n
o
f
o
p
tical
f
lo
w
m
e
th
o
d
th
at
m
ee
ts
t
h
e
co
n
s
tr
ain
ts
a
n
d
s
m
o
o
t
h
n
e
s
s
c
o
n
s
tr
ain
ts
g
lo
b
all
y
.
W
h
i
le
L
K
alg
o
r
ith
m
p
r
o
p
o
s
ed
q
u
ad
r
atic
eq
u
atio
n
o
f
o
p
tical
f
lo
w
w
i
th
t
h
e
s
m
alle
s
t
w
eig
h
t
[
2
0
]
[
2
7
]
[
2
8
]
.
Fu
r
th
er
m
o
r
e,
th
e
o
p
tical
f
lo
w
is
th
e
i
n
s
ta
n
t
an
eo
u
s
v
e
lo
cit
y
o
f
ea
ch
p
ix
e
l i
n
i
m
a
g
e
at
a
ce
r
tai
n
p
o
in
t.
Op
tical
f
lo
w
f
ield
(
o
p
tical
f
lo
w
)
is
d
escr
ib
ed
as a
f
ie
ld
o
f
g
r
a
y
(
g
r
a
y
)
o
f
all
p
ix
els
o
n
t
h
e
i
m
ag
e
o
f
t
h
e
o
b
s
er
v
ed
f
ield
.
T
h
is
o
p
tical
f
l
o
w
f
ield
r
ef
lect
s
t
h
e
r
elati
o
n
s
h
ip
b
et
w
ee
n
th
e
ti
m
e
d
o
m
ai
n
a
n
d
p
o
s
itio
n
ad
j
ac
en
t
f
r
a
m
e
s
o
f
t
h
e
s
a
m
e
p
i
x
el
p
o
s
i
tio
n
[
2
9
]
.
I
n
co
n
s
is
te
n
cies
b
et
w
ee
n
t
h
e
d
ir
ec
tio
n
s
o
f
o
p
tical
f
lo
w
f
ie
ld
an
d
o
p
ti
ca
l
f
lo
w
a
n
d
m
aj
o
r
m
o
v
e
m
e
n
ts
ca
n
b
e
u
s
ed
to
d
etec
t
an
o
b
s
tacle
.
Use
s
o
p
tical
f
lo
w
f
ield
co
m
p
u
t
ed
m
u
lti
-
i
m
ag
e
o
b
tain
ed
f
r
o
m
th
e
s
a
m
e
c
a
m
er
a
at
d
if
f
er
e
n
t
ti
m
e
s
,
an
d
th
e
m
ai
n
m
o
v
e
m
e
n
t
o
f
th
e
ca
m
er
a
in
t
h
e
esti
m
atio
n
b
ased
o
n
o
p
tical
f
lo
w
f
ield
(
o
p
tical
f
lo
w
f
ield
)
.
Op
tical
f
lo
w
ca
n
b
e
g
e
n
er
ated
f
r
o
m
t
w
o
ca
m
er
a
m
o
v
e
m
en
t
s
th
at
f
lo
w
er
a
n
d
f
lo
w
r
o
t
,
if
t
h
e
d
is
tan
ce
o
f
t
h
e
o
b
j
ec
t
in
th
e
f
i
eld
o
f
v
ie
w
a
n
d
t
h
e
ca
m
er
a
is
d
an
d
th
e
an
g
le
b
et
w
ee
n
t
h
e
o
b
j
ec
t
an
d
th
e
d
i
r
ec
tio
n
o
f
tr
an
s
la
tio
n
al
m
o
v
e
m
en
t
is
θ
,
th
e
n
th
e
ca
m
er
a
w
ill
m
o
v
e
w
it
h
tr
an
s
l
atio
n
al
v
elo
cit
y
(
tr
an
s
la
tio
n
al
v
elo
cit
y
)
v
a
n
d
an
g
u
lar
v
elo
cit
y
ω.
Nex
t
o
p
tic
f
lo
w
(
o
p
tical
f
lo
w
)
g
e
n
er
ated
b
y
th
e
o
b
j
ec
t
ca
n
b
e
ca
lcu
late
d
b
y
th
is
eq
u
atio
n
:
[
2
7
]
.
W
h
er
e:
F
=
T
h
e
a
m
o
u
n
t
o
f
o
p
tical
f
lo
w
(
o
p
tical
f
lo
w
)
v
=
v
elo
cit
y
o
r
d
i
s
p
lace
m
e
n
t
t
r
an
s
latio
n
(
tr
an
s
latio
n
al
v
elo
ci
t
y
)
d
=
o
b
j
ec
t in
t
h
e
f
ield
o
f
v
ie
w
o
f
t
h
e
ca
m
e
r
a
+
ω
=
an
g
u
lar
v
elo
cit
y
(
a
n
g
u
lar
v
elo
cit
y
)
θ
=
th
e
d
ir
ec
tio
n
o
f
tr
an
s
latio
n
a
l
m
o
v
e
m
e
n
t is
.
6
.
2
.
Appea
ra
nce
-
B
a
s
ed
T
ec
hn
iq
ues
I
n
th
e
ap
p
ea
r
an
ce
-
b
ased
m
eth
o
d
,
b
asically
d
o
n
e
k
ee
p
i
n
g
in
m
i
n
d
th
e
en
v
ir
o
n
m
e
n
t
b
y
s
a
v
i
n
g
a
s
er
ie
s
o
f
i
m
a
g
es,
w
h
ich
ar
e
u
s
u
all
y
co
n
s
tr
u
cted
f
r
o
m
s
u
b
w
i
n
d
o
w
s
ar
e
ex
tr
ac
ted
b
y
p
er
f
o
r
m
i
n
g
d
o
w
n
-
s
a
m
p
li
n
g
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
RA
I
SS
N:
2089
-
4856
R
ev
iew
o
f V
is
io
n
-
B
a
s
ed
R
o
b
o
t
N
a
vig
a
tio
n
Meth
o
d
(
B
u
d
i R
a
h
ma
n
i)
259
i
m
a
g
es
f
r
o
m
t
h
e
ca
m
er
a,
t
h
en
at
a
s
p
ec
if
ied
ti
m
e,
an
i
m
ag
e
is
ta
k
e
n
a
n
d
s
ca
n
n
ed
o
n
a
lo
n
g
t
h
e
te
m
p
late
th
a
t
h
ad
b
ee
n
p
r
ep
ar
e
d
,
w
h
ic
h
w
il
l
th
en
b
e
k
n
o
w
n
w
h
er
e
th
e
i
m
ag
e
t
h
at
m
atch
e
s
th
e
i
m
a
g
e
th
at
h
a
s
b
ee
n
s
to
r
ed
p
r
ev
io
u
s
l
y
.
I
f
t
h
er
e
ar
e
i
m
a
g
e
s
m
atch
,
th
e
ap
p
r
o
p
r
iate
ac
tio
n
w
i
ll
b
e
d
eter
m
in
ed
f
o
r
p
r
o
p
er
n
av
ig
at
io
n
[
3
0
]
.
T
h
e
ap
p
r
o
ac
h
tak
en
in
th
is
m
eth
o
d
is
th
at
th
e
m
o
d
el
-
b
ased
an
d
v
ie
w
-
b
ased
.
On
t
h
is
m
o
d
el
-
b
ased
ap
p
r
o
ac
h
(
m
o
d
el
-
b
ased
ap
p
r
o
ac
h
)
,
th
e
s
y
s
te
m
is
eq
u
ip
p
ed
w
ith
a
p
r
ev
io
u
s
l
y
k
n
o
w
n
o
b
j
ec
t
m
o
d
el
s
,
in
o
r
d
er
to
r
ec
o
g
n
ize
f
ea
tu
r
es
i
n
a
co
m
p
l
ex
en
v
ir
o
n
m
e
n
t
an
d
to
lo
ca
lize
its
elf
i
n
t
h
e
en
v
ir
o
n
m
e
n
t
[
4
]
.
I
n
th
e
v
ie
w
-
b
ased
ap
p
r
o
ac
h
(
View
-
b
ased
ap
p
r
o
ac
h
)
,
w
h
ic
h
is
n
o
t
u
s
ed
at
all
ex
tr
ac
tio
n
f
e
a
tu
r
es
t
h
at
h
a
v
e
b
ee
n
p
r
ev
io
u
s
l
y
r
ec
o
r
d
e
d
im
a
g
e,
s
el
f
-
lo
ca
lizati
o
n
is
d
o
n
e
w
it
h
i
m
a
g
e
m
atc
h
i
n
g
al
g
o
r
ith
m
s
(
i
m
a
g
e
m
atch
i
n
g
)
[
2
8
]
.
6
.
3
.
Ro
w
B
a
s
ed
T
h
is
m
e
th
o
d
w
a
s
in
tr
o
d
u
ce
d
in
[
3
1
]
th
at
ar
e
im
p
le
m
e
n
ted
o
n
th
e
f
ar
m
r
o
b
o
tic
ap
p
licatio
n
s
in
a
n
o
r
ch
ar
d
.
I
n
th
i
s
m
et
h
o
d
,
th
e
co
lo
r
i
m
a
g
e
ca
p
tu
r
ed
later
c
lu
s
te
r
ed
w
it
h
m
ea
n
-
s
h
if
t a
l
g
o
r
ith
m
.
T
h
e
n
e
w
o
n
t
h
ese
m
et
h
o
d
s
is
th
e
class
if
ica
tio
n
t
ec
h
n
iq
u
e
b
ased
o
n
th
e
th
eo
r
y
o
f
g
r
ap
h
p
ar
titi
o
n
in
g
,
class
if
y
i
n
g
,
cl
u
s
ter
i
n
g
f
o
r
m
th
e
i
m
a
g
e
o
f
a
c
lass
t
h
at
ca
n
b
e
d
ef
in
ed
,
i
n
cl
u
d
in
g
n
a
v
ig
a
ti
o
n
ter
r
ain
,
tr
ee
s
,
a
n
d
s
k
y
[
3
1
]
.
T
h
en
b
y
u
s
i
n
g
t
h
e
Ho
u
g
h
tr
an
s
f
o
r
m
,
i
m
ag
e
e
x
tr
a
cted
m
id
d
le
lan
e
n
ee
d
ed
f
o
r
r
o
b
o
t
n
av
ig
at
io
n
i
n
th
e
g
ar
d
en
[
2
7
]
.
B
y
u
s
i
n
g
t
h
i
s
tech
n
iq
u
e
f
u
r
t
h
er
m
o
r
e
th
e
n
,
t
h
e
m
o
b
ile
r
o
b
o
t
ca
n
ch
an
g
e
a
n
d
i
m
p
r
o
v
e
t
h
e
ab
ilit
y
to
d
ir
ec
t
it
in
ac
co
r
d
an
ce
w
it
h
th
e
d
e
s
ir
ed
p
ath
[
3
1
]
.
Flo
w
c
h
ar
f
r
o
m
t
h
e
m
et
h
o
d
s
h
o
wn
i
n
Fi
g
u
r
e
9
.
Fi
g
u
r
e
6
.
F
lo
w
c
h
ar
t Ro
w
Gu
id
a
n
ce
Nav
i
g
atio
n
[
3
1
]
B
ased
o
n
th
e
ab
o
v
e,
it
ca
n
b
e
s
u
m
m
ar
iz
ed
s
ev
er
al
n
av
i
g
atio
n
m
eth
o
d
s
th
at
h
a
v
e
b
ee
n
d
ev
elo
p
ed
s
in
ce
2
0
1
0
u
n
til n
o
w
,
a
n
d
it is
p
r
esen
ted
i
n
T
ab
le
1
.
7.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
T
ab
le
1
.
Su
m
m
ar
y
o
f
v
is
io
n
-
b
ased
r
o
b
o
t n
av
ig
atio
n
m
et
h
o
d
I
n
d
o
o
r
-
O
u
t
d
o
o
r
C
a
t
e
g
o
r
y
M
e
t
h
o
d
P
a
p
e
r
O
u
t
d
o
o
r
M
a
p
b
a
se
d
O
c
c
u
p
a
n
c
y
G
r
i
d
s
[
7
–
12]
I
n
d
o
o
r
M
a
p
b
a
se
d
h
o
l
o
g
r
a
p
h
y
[
1
3
]
I
n
d
o
o
r
M
a
p
b
u
i
l
d
i
n
g
M
e
t
r
i
c
a
n
d
g
r
i
d
[
1
4
-
1
6
]
I
n
d
o
o
r
M
a
p
b
u
i
l
d
i
n
g
S
c
o
r
e
map
[
1
7
-
1
9
]
I
n
d
o
o
r
M
a
p
b
u
i
l
d
i
n
g
P
o
t
e
n
t
i
a
l
b
a
n
me
t
h
o
d
[
2
0
–
22]
I
n
d
o
o
r
M
a
p
b
u
i
l
d
i
n
g
S
t
e
r
e
o
-
B
a
se
d
[
3
]
[
2
3
]
I
n
d
o
o
r
M
a
p
b
u
i
l
d
i
n
g
S
u
b
-
g
o
a
l
b
a
se
d
[
3
]
[
2
4
-
25]
I
n
d
o
o
r
M
a
p
l
e
ss
O
p
t
i
c
a
l
F
l
o
w
[
2
0
]
[
2
7
-
2
9
]
I
n
d
o
o
r
M
a
p
l
e
ss
A
p
p
e
a
r
a
n
c
e
-
b
a
se
d
t
e
c
h
n
i
q
u
e
[
4
]
[
2
8
]
[
3
0
]
I
n
d
o
o
r
M
a
p
l
e
ss
R
o
w
b
a
se
d
[
2
7
]
[
3
1
]
T
ab
le
1
s
h
o
w
s
t
h
e
s
u
m
m
ar
y
o
f
n
a
v
i
g
atio
n
m
e
th
o
d
b
ased
o
n
m
ap
-
b
ased
,
m
ap
-
b
u
ild
in
g
,
an
d
m
ap
less
n
av
i
g
atio
n
.
Ma
n
y
o
f
n
a
v
i
g
ati
o
n
m
et
h
o
d
s
i
s
m
ap
-
b
u
i
ld
in
g
b
ased
.
B
esid
es
m
ap
les
s
n
a
v
i
g
atio
n
is
o
n
e
o
f
th
e
p
o
p
u
lar
ca
teg
o
r
y
o
f
in
.
8.
CO
NCLU
SI
O
N
A
cc
o
r
d
in
g
to
th
e
s
u
m
m
ar
y
o
f
t
h
e
n
a
v
i
g
atio
n
m
eth
o
d
s
ab
o
v
e,
m
ea
n
w
h
i
le
t
h
e
m
ap
-
b
u
ild
in
g
b
ased
n
av
i
g
atio
n
is
t
h
e
m
eth
o
d
th
at
m
an
y
r
esear
c
h
er
co
n
ce
n
t o
n
.
RE
F
E
R
E
NC
E
S
[1
]
F
.
Bo
n
in
-
f
o
n
t,
A
.
Ortiz,
G
.
Oliv
e
r,
F
.
B.
A
lb
e
rto
,
a
n
d
O.
G
a
b
riel,
“
V
is
u
a
l
Na
v
ig
a
ti
o
n
f
o
r
M
o
b
il
e
Ro
b
o
ts:
A
S
u
rv
e
y
,
”
J
.
In
tell.
R
o
b
o
t.
S
y
st.
,
v
o
l.
5
3
,
n
o
.
3
,
p
p
.
2
6
3
–
2
9
6
,
2
0
0
8
.
[2
]
S
.
Kim
,
H.
Ch
e
o
n
g
,
D.
H.
Kim
,
a
n
d
S
.
K.
P
a
rk
,
“
Co
n
tex
t
-
b
a
se
d
o
b
jec
t
re
c
o
g
n
it
i
o
n
f
o
r
d
o
o
r
d
e
te
c
ti
o
n
,
”
i
n
IEE
E
1
5
t
h
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Ad
v
a
n
c
e
d
R
o
b
o
ti
c
s:
Ne
w
Bo
u
n
d
a
rie
s
fo
r
Ro
b
o
ti
c
s,
ICAR
2
0
1
1
,
2
0
1
1
,
p
p
.
1
5
5
–
1
6
0
.
[3
]
N.
Nir
m
a
l
S
in
g
h
,
A
.
Ch
a
tt
e
rje
e
,
A
.
Ch
a
tt
e
rje
e
,
a
n
d
A
.
Ra
k
sh
it
,
“
A
t
w
o
-
l
a
y
e
r
e
d
su
b
g
o
a
l
b
a
se
d
m
o
b
il
e
ro
b
o
t
n
a
v
ig
a
ti
o
n
a
lg
o
rit
h
m
w
it
h
v
isio
n
s
y
ste
m
a
n
d
IR
se
n
so
rs,”
M
e
a
s.
J
.
In
t.
M
e
a
s.
Co
n
fed
.
,
v
o
l.
4
4
,
n
o
.
4
,
p
p
.
6
2
0
–
6
4
1
,
2
0
1
1
.
[4
]
A
.
Ch
a
tt
e
rjee
,
A
.
Ra
k
sh
it
,
a
n
d
N.
N.
S
in
g
h
,
Vi
si
o
n
Ba
se
d
A
u
t
o
n
o
mo
u
s R
o
b
o
t
N
a
v
ig
a
ti
o
n
.
S
p
ri
n
g
e
r
US,
2
0
1
3
.
[5
]
D.
O.
S
a
les
,
L
.
C.
F
e
rn
a
n
d
e
s,
F
.
S
.
Os
ó
ri
o
,
a
n
d
D.
F
.
W
o
lf
,
“
F
S
M
-
b
a
se
d
V
isu
a
l
Na
v
ig
a
ti
o
n
f
o
r
A
u
to
n
o
m
o
u
s
V
e
h
icle
s,” n
o
.
V
iC
o
M
o
R,
p
p
.
3
7
–
4
2
,
2
0
1
2
.
[6
]
H.
Ry
u
a
n
d
W
.
K.
Ch
u
n
g
,
“
L
o
c
a
l
m
a
p
-
b
a
se
d
e
x
p
lo
ra
ti
o
n
f
o
r
m
o
b
il
e
ro
b
o
ts,
”
In
tell.
S
e
rv
.
Ro
b
o
t
.
,
v
o
l.
6
,
n
o
.
4
,
p
p
.
199
–
2
0
9
,
2
0
1
3
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4856
IJ
RA
Vo
l.
4
,
No
.
4
,
Decem
b
er
2
0
1
5
:
2
5
4
–
2
6
1
260
[7
]
K.
S
u
,
T
.
P
h
a
n
,
C.
Ya
n
g
,
a
n
d
W
.
W
a
n
g
,
“
I
m
a
g
e
-
Ba
se
d
S
m
o
o
th
P
a
th
P
lan
n
in
g
f
o
r
W
h
e
e
led
Ro
b
o
t
,
”
p
p
.
2
0
3
–
2
0
7
,
2
0
1
4
.
[8
]
J.
Je
ss
u
p
,
S
.
N.
G
iv
ig
i,
a
n
d
A
.
Be
a
u
li
e
u
,
“
Ro
b
u
st
a
n
d
Ef
f
icie
n
t
M
u
lt
ir
o
b
o
t
3
-
D
M
a
p
p
i
n
g
M
e
rg
in
g
W
it
h
Oc
tree
-
Ba
se
d
Oc
c
u
p
a
n
c
y
G
rid
s,”
IEE
E
,
p
p
.
1
–
1
0
,
2
0
1
5
.
[9
]
K.
M
.
V
a
ra
d
a
ra
jan
,
“
T
o
p
o
lo
g
ica
l
M
a
p
p
i
n
g
f
o
r
Ro
b
o
t
Na
v
ig
a
ti
o
n
u
sin
g
Aff
o
rd
a
n
c
e
F
e
a
tu
re
s,” p
p
.
4
2
–
4
9
,
2
0
1
5
.
[1
0
]
R.
L
.
Kl
a
se
r
a
n
d
D.
W
o
l
f
,
“
V
isio
n
-
b
a
se
d
a
u
t
o
n
o
m
o
u
s
n
a
v
ig
a
ti
o
n
w
it
h
a
p
ro
b
a
b
il
isti
c
o
c
c
u
p
a
n
c
y
m
a
p
o
n
u
n
stru
c
t
u
re
d
sc
e
n
a
ri
o
s
,
”
2
0
1
4
.
[1
1
]
C.
H.
Yu
n
,
Y.
S
.
M
o
o
n
,
a
n
d
N.
Y.
Ko
,
“
V
isio
n
b
a
se
d
n
a
v
ig
a
ti
o
n
f
o
r
g
o
lf
b
a
ll
c
o
ll
e
c
ti
n
g
m
o
b
il
e
ro
b
o
t,
”
I
n
t.
C
o
n
f.
Co
n
tro
l.
A
u
to
m
.
S
y
st.
,
n
o
.
Ic
c
a
s,
p
p
.
2
0
1
–
2
0
3
,
2
0
1
3
.
[1
2
]
D.
O.
S
a
les
a
n
d
F
.
S
.
Os
ó
rio
,
“
V
i
sio
n
-
b
a
se
d
a
u
t
o
n
o
m
o
u
s
to
p
o
l
o
g
ica
l
n
a
v
ig
a
ti
o
n
i
n
o
u
td
o
o
r
e
n
v
iro
n
m
e
n
ts,
”
Pro
c
.
-
2
0
1
2
Br
a
zili
a
n
R
o
b
o
t.
S
y
mp
.
L
a
t.
Am.
Ro
b
o
t
.
S
y
mp
.
S
BR
-
L
AR
S
2
0
1
2
,
p
p
.
9
1
–
9
6
,
2
0
1
2
.
[1
3
]
P
.
W
u
,
L
.
Ko
n
g
,
a
n
d
S
.
Ga
o
,
“
H
o
lo
g
ra
p
h
y
m
a
p
f
o
r
h
o
m
e
ro
b
o
t:
A
n
o
b
jec
t
-
o
rien
ted
a
p
p
r
o
a
c
h
,
”
In
t
e
ll
.
S
e
rv
.
Ro
b
o
t
.
,
v
o
l.
5
,
n
o
.
3
,
p
p
.
1
4
7
–
1
5
7
,
2
0
1
2
.
[1
4
]
K.
M
o
ri
o
k
a
a
n
d
S
.
Ya
m
a
n
a
k
a
,
“
S
im
p
li
f
ied
m
a
p
re
p
re
se
n
tatio
n
a
n
d
m
a
p
lea
rn
in
g
sy
ste
m
f
o
r
a
u
to
n
o
m
o
u
s
n
a
v
ig
a
ti
o
n
o
f
m
o
b
il
e
ro
b
o
ts,
”
p
p
.
2
5
–
3
5
,
2
0
1
4
.
[1
5
]
L
.
C.
W
.
d
e
S
.
J.
Z.
M
e
n
g
,
“
3
D
V
isu
a
l
S
L
A
M
f
o
r
a
n
A
s
sistiv
e
Ro
b
o
t
in
I
n
d
o
o
r
En
v
iro
n
m
e
n
ts
Us
in
g
RG
B
-
D
Ca
m
e
r
a
s,” in
T
h
e
9
t
h
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Co
mp
u
ter
S
c
ien
c
e
&
Ed
u
c
a
ti
o
n
(
ICCS
E
2
0
1
4
)
,
2
0
1
4
,
p
p
.
3
2
–
3
7
.
[1
6
]
S
.
Na
g
a
p
p
a
,
N.
P
a
l
o
m
e
ra
s,
C.
S
.
L
e
e
,
N.
G
ra
c
i
a
s,
D.
E.
Clar
k
,
a
n
d
J.
S
a
lv
i,
“
S
in
g
le
c
lu
ste
r
P
HD
S
L
A
M
:
A
p
p
li
c
a
ti
o
n
to
a
u
to
n
o
m
o
u
s
u
n
d
e
rw
a
t
e
r
v
e
h
icle
s
u
sin
g
ste
re
o
v
isi
o
n
,
”
Oc
e
a
n
.
2
0
1
3
M
T
S
/
IEE
E
Be
rg
e
n
Ch
a
ll
e
n
g
e
s
No
rth
.
Dime
n
s
.
,
n
o
.
Re
f
2
8
8
2
7
3
,
2
0
1
3
.
[1
7
]
K.
Y.
L
e
e
,
G
.
Y.
S
o
n
g
,
J.
M
.
P
a
rk
,
a
n
d
J.
W
.
L
e
e
,
“
S
tere
o
V
isio
n
En
a
b
li
n
g
F
a
st
Esti
m
a
ti
o
n
Of
F
re
e
S
p
a
c
e
On
T
ra
ff
ic Ro
a
d
s F
o
r
A
u
to
n
o
m
o
u
s Na
v
ig
a
ti
o
n
,
”
v
o
l.
1
6
,
n
o
.
1
,
p
p
.
1
0
7
–
1
1
5
,
2
0
1
5
.
[1
8
]
S
.
A
b
d
u
r
a
n
d
R.
M
a
g
ra
b
i,
“
S
i
m
m
u
latio
n
o
f
Co
ll
it
io
n
A
v
o
id
a
n
c
e
B
y
Na
v
ig
a
ti
o
n
A
ss
ist
a
n
c
e
Us
in
g
S
tere
o
V
isio
n
,
”
p
p
.
5
8
–
6
1
,
2
0
1
5
.
[1
9
]
R.
C.
Leish
m
a
n
,
T
.
W
.
M
c
Lain
,
a
n
d
R.
W
.
B
e
a
rd
,
“
Re
lati
v
e
n
a
v
ig
a
ti
o
n
a
p
p
ro
a
c
h
f
o
r
v
isio
n
-
b
a
se
d
a
e
rial
G
P
S
-
d
e
n
ied
n
a
v
ig
a
ti
o
n
,
”
J
.
I
n
tell.
Ro
b
o
t.
S
y
st.
T
h
e
o
ry
Ap
p
l.
,
v
o
l.
7
4
,
n
o
.
1
–
2
,
p
p
.
9
7
–
1
1
1
,
2
0
1
4
.
[2
0
]
Q.
Zh
a
n
g
,
D.
Ch
e
n
,
a
n
d
T
.
Ch
e
n
,
“
A
n
Ob
sta
c
le
Av
o
id
a
n
c
e
M
e
th
o
d
o
f
S
o
c
c
e
r
Ro
b
o
t
Ba
se
d
o
n
Ev
o
l
u
ti
o
n
a
ry
A
rti
f
icia
l
P
o
ten
ti
a
l
F
iel
d
,
”
E
n
e
rg
y
Pro
c
e
d
ia
,
v
o
l.
1
6
,
p
p
.
1
7
9
2
–
1
7
9
8
,
2
0
1
2
.
[2
1
]
Y.
L
.
T
in
g
a
n
d
J.
S
.
L
iu
,
“
Ef
f
icie
n
t
p
a
th
p
lan
n
in
g
w
it
h
li
m
it
c
y
c
le
a
v
o
id
a
n
c
e
f
o
r
m
o
b
il
e
ro
b
o
t
n
a
v
ig
a
ti
o
n
,
”
in
2
0
1
3
IEE
E
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
M
e
c
h
a
tro
n
ics
a
n
d
A
u
t
o
ma
ti
o
n
,
IEE
E
ICM
A
2
0
1
3
,
2
0
1
3
,
p
p
.
5
0
0
–
5
0
6
.
[2
2
]
F
.
A
d
ib
Ya
g
h
m
a
ie,
A
.
M
o
b
a
rh
a
n
i
,
a
n
d
H.
D.
T
a
g
h
irad
,
“
S
tu
d
y
o
f
p
o
ten
ti
a
l
b
a
n
m
e
th
o
d
f
o
r
m
o
b
il
e
ro
b
o
t
n
a
v
ig
a
ti
o
n
in
d
y
n
a
m
ic en
v
iro
n
m
e
n
t,
”
in
Po
we
r E
lec
tro
n
ics
,
Dr
ive
S
y
ste
ms
a
n
d
T
e
c
h
n
o
l
o
g
ies
Co
n
fer
e
n
c
e
(
PE
DS
T
C),
2
0
1
3
4
t
h
,
2
0
1
3
,
p
p
.
5
3
5
–
5
4
0
.
[2
3
]
H.
S
o
lt
a
n
i,
H.
D.
T
a
g
h
irad
,
a
n
d
a
.
R.
No
ro
u
z
z
a
d
e
h
Ra
v
a
ri,
“
S
ter
e
o
-
b
a
se
d
v
isu
a
l
n
a
v
ig
a
ti
o
n
o
f
m
o
b
il
e
r
o
b
o
ts
in
u
n
k
n
o
w
n
e
n
v
iro
n
m
e
n
ts,
”
2
0
t
h
Ira
n
.
Co
n
f.
El
e
c
tr.
E
n
g
.
,
p
p
.
9
4
6
–
9
5
1
,
2
0
1
2
.
[2
4
]
H.
G
h
a
z
o
u
a
n
i,
L
.
M
a
n
o
u
b
a
,
a
n
d
C.
U.
De
L
a
,
“
Ro
b
o
t
Na
v
ig
a
ti
o
n
M
a
p
Bu
il
d
i
n
g
Us
in
g
S
tere
o
V
i
sio
n
Ba
se
d
3
D
Oc
c
u
p
a
n
c
y
G
rid
,
”
v
o
l.
1
,
p
p
.
6
3
–
7
2
,
2
0
1
0
.
[2
5
]
J.
S
.
Ch
ian
g
,
C.
H.
Hs
ia,
a
n
d
H.
W
.
Hs
u
,
“
A
ste
r
e
o
v
isio
n
-
b
a
se
d
se
lf
-
lo
c
a
li
z
a
ti
o
n
s
y
ste
m
,
”
IEE
E
S
e
n
s.
J
.
,
v
o
l.
1
3
,
n
o
.
5
,
p
p
.
1
6
7
7
–
1
6
8
9
,
2
0
1
3
.
[2
6
]
M
.
L
.
W
a
n
g
,
J.
R.
W
u
,
L
.
W
.
K
a
o
,
a
n
d
H.
Y.
L
in
,
“
De
v
e
lo
p
m
e
n
t
o
f
a
v
isio
n
sy
ste
m
a
n
d
a
stra
teg
y
si
m
u
lato
r
f
o
r
m
id
d
le
siz
e
so
c
c
e
r
ro
b
o
t,
”
i
n
2
0
1
3
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
A
d
v
a
n
c
e
d
Ro
b
o
t
ics
a
n
d
In
telli
g
e
n
t
S
y
ste
ms
,
AR
I
S
2
0
1
3
-
Co
n
fer
e
n
c
e
Pro
c
e
e
d
in
g
s
,
2
0
1
3
,
p
p
.
5
4
–
5
8
.
[2
7
]
Q.
W
u
a
n
d
J.
W
e
i,
“
Re
se
a
r
c
h
P
ro
g
re
ss
o
f
Ob
sta
c
l
e
De
tec
ti
o
n
Ba
se
d
o
n
M
o
n
o
c
u
lar
V
isi
o
n
,
”
2
0
1
4
.
[2
8
]
N.
Oh
n
is
h
i
a
n
d
A
.
I
m
i
y
a
,
“
A
p
p
e
a
ra
n
c
e
-
b
a
se
d
n
a
v
ig
a
ti
o
n
a
n
d
h
o
m
in
g
f
o
r
a
u
to
n
o
m
o
u
s
m
o
b
il
e
ro
b
o
t,
”
Ima
g
e
Vi
s.
Co
mp
u
t
.
,
v
o
l
.
3
1
,
n
o
.
6
–
7
,
p
p
.
5
1
1
–
5
3
2
,
2
0
1
3
.
[2
9
]
Y.
Zh
o
u
,
G
.
Jia
n
g
,
G
.
X
u
,
X
.
W
u
,
a
n
d
L
.
Kru
n
d
e
l,
“
Kin
e
c
t
De
p
t
h
Im
a
g
e
Ba
se
d
Do
o
r
De
te
c
ti
o
n
fo
r
A
u
to
n
o
m
o
u
s
In
d
o
o
r
Na
v
ig
a
ti
o
n
,
”
p
p
.
0
–
5
,
2
0
1
4
.
[3
0
]
K.
Ch
o
i
,
S
.
T
a
n
a
th
o
n
g
,
H.
Kim
,
a
n
d
I.
L
e
e
,
“
Re
a
lt
i
m
e
I
m
a
g
e
M
a
tc
h
in
g
f
o
r
Visio
n
Ba
se
d
Ca
r
Na
v
ig
a
ti
o
n
w
it
h
B
u
il
t
-
in
S
e
n
s
o
ry
Da
ta,” v
o
l.
II,
n
o
.
No
v
e
m
b
e
r,
p
p
.
1
–
6
,
2
0
1
3
.
[3
1
]
M
.
S
h
a
rif
i
a
n
d
X
.
Ch
e
n
,
“
A
No
v
e
l
V
isio
n
Ba
se
d
Ro
w
G
u
id
a
n
c
e
A
p
p
ro
a
c
h
f
o
r
N
a
v
ig
a
ti
o
n
o
f
A
g
ri
c
u
lt
u
ra
l
M
o
b
il
e
Ro
b
o
ts
in
Orc
h
a
rd
s,” p
p
.
2
5
1
–
2
5
5
,
2
0
1
5
.
B
I
B
L
I
O
G
R
AP
H
Y
O
F
AUT
H
O
RS
Bu
d
i
Ra
h
m
a
n
i,
re
c
e
iv
e
d
h
is
b
a
c
h
e
lo
r’s
o
f
El
e
c
tri
c
a
l
En
g
g
in
e
rin
g
,
a
n
d
M
a
ste
r
o
f
In
f
o
rm
a
ti
c
s
f
ro
m
Yo
g
y
a
k
a
rta
S
tate
Un
iv
e
r
sity
a
n
d
Dia
n
Nu
s
w
a
n
to
ro
Un
iv
e
rsit
y
in
2
0
0
3
a
n
d
2
0
1
0
re
sp
e
c
ti
v
e
l
y
.
Cu
rre
n
tl
y
h
e
is
a
d
o
c
t
o
ra
l
stu
d
e
n
t
a
t
De
p
a
rtm
e
n
t
o
f
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
El
e
c
tro
n
ics
,
G
a
d
jah
M
a
d
a
U
n
iv
e
rsity
sin
c
e
2
0
1
4
.
H
e
w
a
s
in
tere
st
in
g
in
Em
b
e
d
d
e
d
S
y
ste
m
a
n
d
Ro
b
o
ti
c
s
.
Cu
rre
n
tl
y
h
is
re
se
a
r
c
h
f
o
c
u
se
d
is
c
o
m
p
u
ter
v
isio
n
a
n
d
c
o
n
tro
l
sy
ste
m
f
o
r
ro
b
o
t.
His
o
th
e
r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
d
e
c
isio
n
su
p
p
o
rt
sy
ste
m
u
sin
g
a
rti
f
icia
l
n
e
u
ra
l
n
e
t
w
o
rk
.
He
c
a
n
b
e
c
o
n
tac
ted
b
y
e
m
a
il
:
b
u
d
irah
m
a
n
i@g
m
a
il
.
c
o
m
h
tt
p
:/
/
b
u
d
irah
m
a
n
i.
w
o
rd
p
re
ss
.
c
o
m
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
RA
I
SS
N:
2089
-
4856
R
ev
iew
o
f V
is
io
n
-
B
a
s
ed
R
o
b
o
t
N
a
vig
a
tio
n
Meth
o
d
(
B
u
d
i R
a
h
ma
n
i)
261
Ag
f
ian
to
Ek
o
P
u
tra
re
c
e
iv
e
d
h
is
b
a
c
h
e
lo
r’s,
m
a
ste
r,
a
n
d
d
o
c
t
o
ra
l
d
e
g
re
e
in
1
9
9
2
,
1
9
9
8
,
a
n
d
2
0
1
0
f
ro
m
Ga
d
jah
M
a
d
a
Un
iv
e
rsit
y
I
n
d
o
n
e
sia
re
sp
e
c
ti
v
e
l
y
.
His
r
e
se
a
r
c
h
in
tere
sts
li
e
in
th
e
f
ield
o
f
d
ig
it
a
l
sig
n
a
l
p
ro
c
e
ss
in
g
,
e
m
b
e
d
d
e
d
e
lec
tro
n
ics
,
a
n
d
sa
telli
te
s
y
ste
m
.
He
is
fo
u
n
d
e
r
o
f
P
INT
A
R
EM
BEDDED
S
YST
EM
g
ro
u
p
i
n
F
a
c
e
b
o
o
k
w
it
h
m
o
re
th
a
n
3
2
0
0
m
e
m
b
e
r
(No
p
e
m
b
e
r
2
0
1
3
)
.
He
is
o
n
e
o
f
Per
so
n
i
n
C
h
a
rg
e
o
f
INSP
IR
E
(
IiNUSA
T
-
1
)
In
d
o
n
e
si
a
sin
c
e
2
0
1
0
a
n
d
c
h
a
irm
a
n
o
f
P
3
S
a
t
(
P
u
sa
t
P
e
n
e
li
ti
a
n
d
a
n
P
e
n
g
e
m
b
a
n
g
a
n
S
a
telit
)
-
Un
iv
e
r
sitas
G
a
d
jah
M
a
d
a
,
Yo
g
y
a
k
a
rta.
H
e
c
a
n
b
e
c
o
n
tac
ted
b
y
e
m
a
il
:
a
g
f
i6
8
@g
m
a
il
.
c
o
m
h
tt
p
:
//
a
g
f
i.
sta
ff
.
u
g
m
.
a
c
.
id
/b
lo
g
/i
n
d
e
x
.
p
h
p
/ab
o
u
t/
Ag
u
s Ha
rjo
k
o
re
c
e
iv
e
d
h
is
b
a
c
h
e
l
o
r’s
d
e
g
re
e
in
1
9
8
6
Un
iv
e
rsitas
Ga
d
jah
M
a
d
a
,
In
d
o
n
e
sia
;
h
is
m
a
ste
r
d
e
g
r
e
e
in
1
9
9
0
f
ro
m
Un
iv
e
rsit
y
o
f
Ne
w
Bru
n
s
w
ick
,
C
a
n
a
d
a
;
a
n
d
h
is
d
o
c
to
ra
l
d
e
g
re
e
in
1
9
9
6
f
ro
m
Un
iv
e
rsit
y
o
f
Ne
w
Bru
n
sw
ick
,
Ca
n
a
d
a
.
S
i
n
c
e
1
9
8
7
h
e
h
a
s
b
e
e
n
a
lec
t
u
re
r
a
n
d
a
re
se
a
rc
h
e
r
a
t
th
e
d
e
p
a
rtm
e
n
t
o
f
Co
m
p
u
ter S
c
ien
c
e
a
n
d
E
lec
tro
n
ics
,
Un
iv
e
rsitas
G
a
d
jah
M
a
d
a
.
His
re
se
a
rc
h
in
tere
sts
li
e
in
th
e
f
ield
o
f
Dig
it
a
l
I
m
a
g
e
P
ro
c
e
ss
in
g
,
M
a
c
h
in
e
V
isi
o
n
,
S
e
n
so
r
Ne
tw
o
rk
,
M
u
lt
im
e
d
ia
IR
(I
m
a
g
e
,
A
u
d
io
,
V
i
d
e
o
P
ro
c
e
ss
in
g
).
He
c
a
n
b
e
c
o
n
tac
ted
b
y
e
m
a
il
:
a
h
a
rjo
k
o
@u
g
m
.
a
c
.
id
h
tt
p
:/
/ac
a
d
sta
ff
.
u
g
m
.
a
c
.
id
/ah
a
rjo
k
o
T
ri
Ku
n
to
ro
P
riy
a
m
b
o
d
o
c
u
rre
n
t
ly
h
e
is
a
n
A
s
so
c
it
a
te
P
ro
f
e
ss
o
r
a
t
De
p
a
rt
m
e
n
t
o
f
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
El
e
c
tro
n
ics
G
a
d
jah
M
a
d
a
Un
iv
e
rsit
y
.
He
is
a
m
e
m
b
e
r
o
f
IEE
E.
He
is
a
lso
h
o
ld
a
p
o
sisio
n
a
s
a
S
e
c
re
tar
y
o
f
S
a
tell
it
e
a
n
d
A
e
ro
sp
a
c
e
El
e
c
tro
n
ics
Re
se
a
rc
h
G
ro
u
p
,
G
a
d
jah
M
a
d
a
Un
iv
e
rsi
t
y
.
Du
rin
g
2
0
1
0
-
2
0
1
3
h
e
w
a
s
INSP
IRE
Na
ti
o
n
a
l
P
ro
jec
t
L
e
a
d
e
r.
His
re
sp
o
n
sib
il
it
y
w
a
s
c
o
o
rd
i
n
a
ti
n
g
t
h
e
d
e
v
e
lo
p
m
e
n
t
o
f
th
e
F
i
rst
In
d
o
n
e
sia
In
ter
U
n
iv
e
rsity
S
a
telli
te
(IiNUSAT
-
1
),
a
p
ro
jec
t
f
u
n
d
e
d
b
y
Dire
c
to
ra
te
G
e
n
e
ra
l
o
f
Hi
g
h
e
r
Ed
u
c
a
ti
o
n
,
M
i
n
is
try
o
f
Ed
u
c
a
ti
o
n
a
n
d
Cu
tu
re
.
He
a
c
ti
v
e
l
y
jo
in
to
S
m
a
ll
S
a
telli
t
e
S
tan
d
a
riza
ti
o
n
g
ro
u
p
in
Kitak
y
u
sh
u
I
n
stit
u
te
o
f
Tec
h
n
o
lo
g
y
.
A
lso
,
a
c
ti
v
e
in
A
P
S
CO’s
S
m
a
ll
S
tu
d
e
n
t
S
a
telli
te
P
ro
jec
t
M
e
e
ti
n
g
.
Cu
rre
n
tl
y
h
e
c
o
n
d
u
c
ts
re
se
a
rc
h
in
th
e
f
ield
o
f
n
a
n
o
sa
telli
te
a
n
d
A
u
to
n
o
m
o
u
s
Un
m
a
n
n
e
d
S
y
ste
m
s.
His
o
th
e
r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
Co
m
p
u
ter
Ne
two
rk
S
e
c
u
rit
y
,
e
G
o
v
e
rn
m
e
n
t
S
y
st
e
m
s.
He
c
a
n
b
e
c
o
n
tac
ted
b
y
e
m
a
il
:
m
a
stri@u
g
m
.
a
c
.
id
h
tt
p
:
//
a
c
a
d
sta
ff
.
u
g
m
.
a
c
.
id
/m
a
stri
Evaluation Warning : The document was created with Spire.PDF for Python.