In
te
r
n
ation
a
l Jou
rn
al
o
f Po
we
r
Elec
tron
ic
s an
d
D
r
ive S
y
stem
(IJ
PED
S
)
V
o
l.
11, N
o.
1, Mar
ch 20
20,
p
p.
382~
3
8
9
IS
S
N
: 2088-
86
94,
D
O
I
:
10.11
59
1
/ij
ped
s
.
v11
.
i
1.pp
3
82-
38
9
382
Jou
rn
a
l
h
o
me
pa
ge
:
ht
tp:
//
i
j
ped
s
.
i
ae
sc
ore.
c
o
m
Flight cost calcul
ation for
unma
nned air ve
h
icle based on path
length and he
a
di
ng angle change
S
a
n
j
oy
Ku
mar
D
e
b
n
ath
1
,
Ros
li Om
ar
2
,
B.
S
. S.
K
. Ibrah
im
3,
S
u
s
ama
Bagc
h
i
4
,
E
l
ia
N
a
d
i
r
a
5
,
Faisal
A
min
6
, Bashir
Bala
M
u
h
ammad
7
1
,
2,
3,
4,
5,
6
F
acul
t
y
of
Elect
ri
cal
&
E
lec
t
ron
i
cs
En
g
i
n
e
e
rin
g
, Uni
versiti T
un
H
uss
e
in
O
nn
M
a
lay
s
i
a
,
M
a
lay
s
i
a
3
S
c
ho
ol
of M
ech
anical
, A
ero
s
p
a
ce & Au
to
m
o
tiv
e
Eng
i
n
eerin
g
,
Facu
l
t
y
o
f
Eng
i
n
eering
, Env
iron
ment & Co
m
p
u
tin
g
,
Cov
e
nt
ry
U
n
i
versity
,
Unit
ed K
ingd
om
7
S
c
ho
ol
o
f M
echan
ical
En
g
i
n
eerin
g,
N
ort
h
w
e
st
ern
P
o
lyt
echn
i
cal Un
iv
e
r
s
i
ty
,
C
h
i
n
a
Art
i
cl
e In
fo
ABSTRACT
A
r
tic
le hist
o
r
y
:
R
e
c
e
i
v
e
d
Au
g
1
2
,
2
019
Re
vise
d O
c
t
2
8
,
20
1
9
A
c
c
e
pte
d
D
ec 3,
201
9
T
h
i
s
p
a
p
e
r
p
r
o
p
o
s
e
s
a
m
e
t
h
o
d
t
o
c
a
l
c
u
l
a
t
e
a
f
l
i
g
ht
c
o
s
t
o
f
a
n
u
nm
a
n
n
e
d
ae
ria
l
veh
i
cl
e
(UAV
)
co
nsi
d
eri
ng
it
s
ch
ang
e
o
f
h
eadi
ng
angl
e
th
ou
g
h
t
h
ere
are
m
a
ny
r
eas
on
s
th
at
caus
e
t
h
e
e
n
e
rgy
co
ns
um
ptio
n.
T
he
p
ro
po
sed
ap
pro
ach
dem
o
nst
r
ates
t
h
a
t
wh
en
a
UAV
m
o
v
es
from
a
s
t
artin
g
po
siti
on/po
i
nt
t
o
a
targ
et/
goal
p
o
s
i
tio
n
/
poi
n
t
,
if
t
h
e
num
ber
of
o
b
s
t
acle
in
creases
,
t
h
e
nu
mb
er
o
f
head
in
g
ch
ang
e
w
o
u
l
d
a
l
s
o
increase.
A
s
a
r
e
s
u
lt,
i
t
rais
es
t
he
energy
con
s
u
m
p
t
i
o
n
of
t
he
U
A
V
.
It
a
l
s
o
s
hows
th
at
t
h
e
m
ag
nitu
de
o
f
hea
di
ng
chan
ge
w
o
u
l
d
a
ff
ect
t
he
e
nerg
y
con
s
u
m
ption
pro
port
i
o
n
a
l
ly.
The
t
h
eo
retical
anal
ys
is
a
s
well
a
s
t
h
e
sim
u
latio
n
o
ut
com
e
p
rov
e
s
the
us
ef
ulnes
s
of
t
he
p
r
op
ose
d
t
e
c
h
ni
qu
e
.
K
eyw
ord
s
:
Al
go
rit
h
m d
e
ve
l
o
p
m
ent
Au
to
no
mou
s
Cost c
alc
u
la
ti
o
n
Energ
y
e
ff
ic
ie
nt
U
A
V
p
ath p
l
a
n
ni
n
g
Th
is
is a
n
o
p
en acces
s a
r
ti
cle u
n
d
e
r t
h
e
CC
B
Y
-S
A
li
cens
e
.
Corres
pon
d
i
n
g
Au
th
or:
Rosli Om
ar,
Fa
cult
y
o
f
E
l
e
c
t
rica
l
&
Electr
o
n
i
c
En
g
i
neer
i
ng,
U
n
i
v
ersi
ti
T
un
H
u
ssei
n
O
nn
Ma
lays
ia,
P
a
rit Raja,
Bat
u
P
a
h
at-8
64
0
0
,
Johor,
M
a
la
ys
i
a
.
Em
ail:
roslio
@
u
t
h
m.
edu.
my
1.
I
N
TR
OD
U
C
TI
O
N
A
path
p
la
n
n
i
ng
a
ssi
gnm
en
t
usua
l
l
y
t
a
ke
s
seve
ral
i
n
pu
t
va
l
u
es
o
r
pa
r
a
m
e
ter
s
;
suc
h
a
s
a
star
tin
g
pos
it
io
n
/
p
o
i
n
t
o
r
sta
r
t
co
n
f
ig
ura
tio
n
w
h
ic
h
is
a
n
in
it
i
a
l
a
nd
m
a
j
or
c
onfig
ur
at
i
o
n
of
U
A
V
s,
a
goa
l
p
o
s
i
t
i
on/
poi
nt
o
r
go
a
l
c
on
fi
gu
rati
on
w
hi
ch
i
s
t
h
e
b
a
si
c
con
f
ig
u
r
a
t
i
o
n
o
f
a
U
A
V
,
a
n
d
t
h
e
o
b
s
t
a
c
l
e
s
w
h
i
c
h
a
r
e
t
h
e
obj
ects
t
o
be
a
vo
id
ed
b
y
th
e
UAV
wh
i
l
e
t
rav
e
rsin
g
a p
a
t
h
f
r
om
the
sta
rting co
nfi
gura
t
i
o
n/
p
o
in
t to
th
e
g
oa
l
con
f
ig
ura
tio
ns
/
poi
nt.
A
pa
t
h
,
re
l
a
t
i
n
g
t
o
the
s
t
art
i
n
g
c
o
n
fi
gur
a
t
i
o
n
a
n
d
t
h
e
goa
l
c
o
nfi
gura
t
i
on,
c
a
n
b
e
spec
ifie
d
i
n
a
c
on
fi
g
u
rat
i
o
n
spac
e.
M
ore
o
ve
r,
e
xtra
c
on
strai
n
t
s
t
yp
i
c
a
l
l
y
m
a
k
e
t
h
e
m
i
ssi
on
pro
g
re
ssive
ly
c
o
mp
li
cat
ed
lik
e
k
eep
ing
a
sp
ec
ifi
c
d
i
s
t
a
n
ce
t
h
re
shol
d
t
o
t
h
e
o
b
s
tac
l
e
s
o
r
m
oving
in
o
n
l
y
o
n
e
d
i
rec
t
i
on
e
t
c
.
A
p
a
th
-pl
a
nnin
g
algo
ri
th
m
f
o
r
a
mov
i
ng
UAV,
b
y
i
t
s
o
wn
s
t
r
at
e
g
i
es,
mu
st
a
vo
i
d
t
h
e
o
bst
a
cles
t
o
ma
int
a
in
s
afe
t
y
.
A
U
A
V
has
a
va
st
u
sa
b
ili
ty.
The
i
r
a
g
i
lit
y
p
r
om
otes
t
hem
t
o
b
e
e
nga
ge
d
in
n
um
erous
s
ur
v
e
illa
nc
e
and
pub
lic rela
t
e
d
w
or
ks,
suc
h
as, loca
l
i
t
i
e
s [1]
an
d w
ild
l
i
fe
observ
i
ng [2]
, sear
ch a
s w
e
l
l
as r
e
scue
oper
a
tio
ns
[3],
a
n
d
a
ls
o
in
c
ul
tiva
t
i
o
n
[
4
].
N
AS
A
fi
r
s
t
tim
e
b
u
il
t
a
n
d
tes
te
d
unma
nne
d
a
e
ro
na
ut
ic
a
l
f
r
a
m
e
w
o
rk
f
or
its
safe
a
nd com
p
eten
t
low
-
alti
tu
de
a
irspac
e tra
f
fic
m
a
nage
me
n
t
[
5]
.
J.
G
iesbre
cht
a
n
d
D
e
fe
nse
R&D
Cana
da
u
s
e
d
a
syn
o
p
s
i
s
of
h
i
gh-
le
v
e
l
pa
t
h
p
l
a
nn
ing
me
t
h
od
s
and
su
rv
ey
ed
a
l
l
b
it
s
of
t
h
e
p
a
t
h
pl
a
nni
ng
p
ro
ce
du
re
a
s
wel
l
a
s
w
o
r
ld
r
e
p
rese
nta
t
i
on, gra
ph sea
r
ch alg
ori
t
hm
s, an
d
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
E
l
e
c
&
D
ri S
yst
IS
S
N
:
2088-
86
94
F
lig
h
t
cost c
a
lc
ul
ati
o
n fo
r un
m
a
n
n
ed
a
i
r
ve
hic
l
e
b
a
se
d
on
pa
th
len
g
t
h a
n
d
he
a
d
in
g
(Sa
n
j
oy
Kum
a
r D
e
bn
a
t
h)
38
3
pla
n
ni
ng
for
pa
rtl
y
a
n
d
e
ntir
e
l
y
i
n
de
fin
ite
e
nv
iro
n
m
e
n
t
s
[6].
P
l
a
nn
ing
repre
s
enta
t
i
ons
s
uc
h
as
R
oa
d
m
aps
Tec
h
niq
u
e
(R
M),
Cel
l
D
eco
m
pos
i
t
i
ons
(
CD
)
a
nd
P
o
t
e
nti
a
l
F
i
e
l
ds
(
P
F
)
a
l
o
n
g
s
i
de
h
eur
i
s
t
i
c
a
s
w
e
l
l
a
s
no
n-
heur
ist
i
c
m
e
t
h
ods
o
f
gra
ph
s
e
a
r
ch
w
er
e
c
overe
d.
R
e
c
e
n
tl
y,
a
dva
n
c
e
d
a
nd
w
i
de
spr
ead
a
lg
ori
t
hms
w
e
re
a
l
s
o
exa
m
ine
d
s
uc
h
as
A
*
t
h
en
D
*,
P
ote
n
ti
a
l
F
i
e
lds
(P
F
)
,
Ra
p
i
d
l
y
E
x
p
lor
i
ng
R
a
n
dom
Trees
(R
RT)
and
Pr
ob
a
b
ilis
tic
R
oadm
aps
(PR
M
)
[6,
7].
Class
i
c
me
tho
d
s
ha
ve
num
er
ous
s
h
o
r
t
c
o
ming
s,
like
hi
gh
tim
e
c
o
m
p
l
e
x
i
t
y
w
i
t
h
h
i
g
h
d
i
m
e
n
s
i
o
n
s
,
a
n
d
o
c
c
u
r
r
e
n
c
e
o
f
l
o
c
a
l
m
i
n
i
m
a
,
and
he
nc
e,
t
hese
a
lg
ori
t
h
m
s
ar
e
inc
o
m
p
e
t
e
n
t.
S
o,
t
o
ma
ke
t
he
c
lass
ic
m
et
ho
ds
p
rofic
i
e
n
t,
p
ro
bab
i
list
i
c
a
l
gor
ithm
s
w
e
r
e
use
d
w
i
t
h
P
R
M
a
n
d
RRT
t
o
r
eap
t
he
f
or
em
ost
a
d
van
t
a
g
e
o
f
h
i
g
h-spee
d
imp
l
e
m
entat
i
o
n
.
T
o
s
o
l
v
e
t
h
e
p
r
o
b
l
e
m
o
f
l
o
c
a
l
m
i
n
i
m
a
,
ma
ny
he
uris
ti
c
s
a
s
w
e
ll
a
s
meta
-he
u
ris
t
i
c
a
l
gor
ithm
s
w
ere
used
in
r
o
b
o
t
m
oti
on
p
l
a
n
ning
.
For
inst
a
n
ce,
a
com
b
i
n
a
t
i
o
n
o
f
t
he
P
F
a
nd
S
i
mulate
d
A
n
nea
l
ing
(S
A
)
t
echn
i
que
w
a
s
the
rem
e
dy
of
t
h
i
s
pro
b
l
em
.
F
u
r
t
h
e
r
appr
oa
ches
w
e
r
e
G
e
net
i
c
Al
g
o
ri
thms
(
GA
),
A
r
t
ific
i
a
l
N
e
ura
l
N
e
t
w
o
r
k
(ANN),
P
a
rt
i
c
l
e
S
wa
r
m
O
p
t
i
m
izati
o
n
(P
S
O
),
W
ave
l
e
t
T
he
ory,
A
n
t
C
o
l
on
y
(
A
CO
)
a
n
d
F
u
z
z
y
L
o
gi
c
(
F
L).
H
e
u
rist
ic
a
l
gor
it
hms
ne
ve
r
gi
ve
assura
n
c
e
to
f
ind
a
so
lut
i
o
n,
b
u
t
i
f
t
h
e
y
(
alg
o
ri
th
m
s
)
do,
i
t
i
s
e
x
pec
t
e
d
t
o
be
m
ore
r
a
pid
tha
n
t
he
d
e
t
er
m
i
nist
ic
appr
oa
ches
[
8].
2.
E
N
E
R
GY
E
FFICIENT
P
A
T
H
PL
ANNING
I
SSUES
En
ergy
e
ffi
ci
en
t
p
a
th
p
l
a
nnin
g
i
s
a
c
o
mp
l
e
x
su
b
j
ect
.
M
a
n
y
e
nti
t
ies
ne
e
d
t
o
be
m
e
a
sured
for
ca
l
c
u
l
a
tin
g
the
ener
g
y
e
ffic
i
e
n
t
pa
th
p
lan
n
i
ng.
S
ome
of
t
he
m
st
a
t
e
d
b
e
l
o
w
a
r
e
u
s
u
a
l
l
y
c
o
n
s
i
d
e
r
e
d
i
n
t
h
e
ene
r
g
y
c
o
s
t
ca
l
c
ula
t
io
n for
op
tima
l
e
ner
gy ef
fic
i
e
n
t pa
th
p
la
nn
ing
co
nce
r
n
:
i.
Path Distan
c
e
Co
mp
l
e
t
i
o
n
of
a
m
i
s
sio
n
d
epen
ds
o
n
th
e
arri
v
a
l
of
a
UAV
to
a
t
a
rg
et
poin
t
a
ft
e
r
g
oi
n
g
t
h
r
ou
gh
t
h
e
p
l
ann
e
d
wa
ypoi
nt
s
.
T
hu
s
,
t
h
e
c
o
r
e
i
m
po
rt
an
ce
i
s
g
iv
en
t
o
pa
t
h
d
ista
nce
t
h
at
i
s
t
h
e
trave
l
l
e
d
d
i
st
a
n
ce
b
e
t
we
en
the s
t
ar
t
i
n
g
a
n
d
the
t
a
r
get
po
i
n
t.
ii. Pat
h
Tra
vel
Time
Tr
avel
t
i
m
e
is
a
l
s
o
a
n
o
t
her
m
easure
of
o
p
tima
l
e
nerg
y
e
f
f
i
c
i
e
n
t
p
a
t
h
p
l
ann
i
ng
a
l
gor
it
hm.
F
o
r
thi
s
in
sta
n
c
e
,
i
t
c
o
n
s
i
de
rs
t
ha
t
t
h
e
q
u
ic
kes
t
a
n
d
the
sh
orte
st
p
ath
s
a
re
d
i
f
fer
e
nt.
T
h
e
quic
k
e
s
t/fa
s
t
e
s
t
m
ea
ns
t
he
v
e
hi
cl
e
can
r
e
a
c
h
i
t
s
t
arg
e
t
wi
th
i
n
t
h
e
l
east
t
r
av
el
p
e
r
iod
.
T
h
e
qui
ck
est
p
a
t
h
m
ay
n
o
t
b
e
t
h
e
sa
me
a
s
t
h
e
shor
tes
t
p
a
t
h
b
e
ca
u
s
e
o
f
t
he
t
raffi
c
an
d
ha
phaz
a
r
d
i
nc
i
d
e
n
c
e
s
ju
st
a
s
th
e
fly
i
n
g
o
r
dr
i
v
i
n
g
gu
ide
l
i
n
e
s
l
ike
li
m
i
te
d
ra
nge
o
f
s
p
ee
d.
A
dd
i
tio
na
ll
y,
t
he
f
a
s
tes
t
p
a
t
h
m
u
st
b
e
upda
t
e
d
fre
que
n
tly
t
hrou
gh
o
u
t
t
h
e
veh
i
cle
tri
p
a
s
t
ra
f
fi
c
ci
rc
u
m
st
an
c
e
s
c
h
a
n
g
e
q
ui
ck
ly
, p
a
rt
i
c
ul
a
r
l
y
i
n
huge
u
r
ban a
r
ea
s.
ii
i. Path H
e
ad
i
ng Ch
ange
I
f
UAV
t
r
av
el
s
in
a
s
t
r
aig
h
t
pat
h
w
it
ho
u
t
a
ny
o
b
s
t
a
cl
e,
i
t
s
s
p
e
e
d
m
ay
b
e
con
s
ta
n
t
.
Howe
ver,
i
f
the
r
e
is
o
bs
tac
l
e
o
n
t
he
f
l
i
g
h
t
pa
t
h
,
the
U
A
V
n
e
e
d
s
t
o
t
a
k
e
a
s
u
ita
bl
e
a
l
t
e
rn
ati
v
e
r
o
ut
e
a
v
oi
d
i
ng
t
h
e
o
b
s
t
a
c
l
e
by
c
h
an
gi
ng
i
t
s
d
irec
t
i
o
n
s
t
a
rt
i
ng
fro
m
t
h
e
n
e
are
s
t
wa
ypoi
nt
.
Th
er
efor
e,
i
ts
s
pee
d
h
as
t
o
b
e
s
l
o
w
e
d
d
o
w
n
w
hi
le
p
a
ssi
n
g
th
e
way
poi
nt
t
o
ensu
re
i
t
is
c
oll
i
s
ion-f
r
e
e
.
T
h
e
U
A
V
m
a
y
ne
ed
t
o
a
cce
lera
t
e
a
ga
in
a
fte
r
a
v
o
i
d
ing
t
h
e
obs
t
a
c
l
e
t
o
e
n
s
ure
tha
t
t
he
m
ission
is
p
e
r
form
ed
w
it
h
i
n
the
g
i
v
en
tim
e.
E
very
t
i
m
e
the
UAV
c
han
g
e
s
its
s
pee
d
,
it
w
i
l
l
c
a
u
se
e
n
e
r
gy
loss
a
n
d
henc
e,
w
i
t
h
the
i
n
cre
a
si
ng
numbe
r
o
f
o
bs
t
a
cles,
the
loss
w
i
ll
i
n
c
r
ea
se
p
roport
i
o
n
a
l
l
y
.
i
v
. S
a
f
et
y
Mo
st
opt
im
al
e
ner
g
y
e
f
fic
i
e
n
t
pa
th
p
la
n
n
i
n
g
a
l
g
o
r
ithm
s
e
m
pha
si
s
on
the
s
hor
test
p
a
t
h
f
i
nd
i
ng
w
h
e
n
ot
her q
u
a
l
i
t
ies of ser
vi
c
e
al
s
o
deser
v
e a
t
t
e
n
t
i
o
n
suc
h
as
d
i
s
t
a
nc
e, o
bs
t
a
cles
,
ph
ysi
c
a
l
l
im
it
ati
o
ns of the
ve
hic
l
e
,
alg
o
ri
t
h
m
p
l
an
,
e
n
v
i
r
onme
n
t
,
o
p
t
im
al
ity,
co
mple
t
e
ness,
s
p
a
c
e
a
n
d
ti
m
e
c
omple
x
i
t
y,
d
ynam
i
c
s
e
tc.
A
m
on
g
them
, sa
f
ety
is
a
lw
ays t
h
e
firs
t
priori
ty i
n a
UA
V
m
i
ssio
n.
v
.
O
b
stac
l
e
H
o
st
ili
ty
O
b
stac
les’
h
os
t
i
l
ity
i
s
t
h
e
ra
ti
o
b
e
tw
e
e
n
t
he
a
r
ea
bl
ocke
d
b
y
o
bs
tac
l
e
s
i
n
a
g
i
ve
n
fre
e
s
p
ace
a
n
d
t
he
si
z
e
o
f
the
to
ta
l
free
space
a
r
e
a
.
T
o
fi
n
d
t
h
e
a
v
a
i
l
a
b
l
e
p
a
t
h
t
h
a
t
t
h
e
UAV
can
f
o
l
l
o
w,
t
he
d
escrip
ti
o
n
o
f
t
h
e
con
f
ig
ura
tio
n
spa
c
e
is
r
eq
uire
d
[9].
C
o
n
f
i
g
ura
t
i
o
n
spa
c
e
(C-
s
pa
c
e
)
is
t
he
c
om
m
on
idea
b
e
h
in
d
a
l
m
o
st
a
ll
p
a
t
h
pla
n
ni
ng
a
p
proac
h
e
s
a
n
d
i
t
m
a
inl
y
c
ons
ist
s
o
f
three
ele
m
ents
n
a
m
e
l
y
w
orkspac
e
,
free
space
a
n
d
o
bs
t
a
cl
e
[1
0].
T
he
U
A
V
m
ust
hav
e
p
ri
o
r
k
n
o
w
l
e
d
ge
a
bo
u
t
t
he
o
bs
t
acle
ar
ea
and
t
h
e
fre
e
s
pa
ce
so
t
ha
t
it
c
a
n
f
i
nd
its
pat
h
from
start
i
n
g
t
o
ta
rge
t
p
oi
n
t
e
nsur
i
n
g
no
c
o
l
lis
ion.
C
onsi
der
i
ng
t
h
i
s
ma
t
t
e
r
,
con
f
i
g
ura
tio
n
spa
ce
i
s
t
he
are
a
w
her
e
t
he
U
A
V
c
a
n
f
ly
by
av
o
i
d
i
ng
c
o
ll
is
i
o
n
an
d
fi
nd
the
s
hor
t
e
st
p
at
h
an
d,
a
s
a
result,
i
t
c
a
n
sa
ve
ene
r
g
y
. H
e
nc
e, the c
o
n
fi
gura
t
i
on
s
p
ac
e ind
i
c
a
t
e
s
the ac
t
ua
l
obs
t
acl
e
zo
n
e
a
n
d
f
r
ee
s
p
a
c
e
r
eg
i
o
n
fo
r
th
e
t
r
av
e
r
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st V
ol.
11,
N
o.
1
, Ma
r
202
0
:
382
–
38
9
38
4
o
f
UAV.
If
t
h
e
t
o
t
a
l
sear
ch
a
rea
i
s
A
a
nd
t
h
e
t
o
t
al
a
re
a
bl
o
c
k
e
d
b
y
obs
t
a
c
l
es
i
s
Ό
t
hen
the
ob
stacle
s
hostil
ity =
Ό/
A
.
v
i
. W
e
at
her
I
n
o
p
e
n
-
ai
r
fl
igh
t
,
UAVs
d
ist
i
n
c
tly
n
eed
t
o
deal
w
ith
t
h
e
sto
c
h
a
s
t
i
c
of
w
e
a
ther
c
i
r
cum
s
ta
nces
w
h
i
c
h
ca
n
im
pac
t
t
he
e
ner
g
y
fe
e
d
i
n
g
of
U
A
V
s
[11
-
13]
.
These
en
sure
s
e
v
era
l
c
ha
rac
t
erist
i
c
s
t
h
a
t
ca
n
p
o
te
n
t
i
a
lly
a
n
d
pow
er
full
y
in
fl
u
e
n
ce
t
h
e
solu
t
i
o
n
a
p
p
roa
c
h
r
o
u
t
i
n
g
p
ro
bl
e
m
f
or
a
U
A
V
.
T
h
e
r
e
a
r
e
t
w
o
k
e
y
i
s
s
u
e
s
o
f
weat
h
e
r’s
i
n
fl
uen
c
es on
t
h
e UAV mo
v
i
n
g
and
t
h
ey
a
re d
escri
b
ed
b
e
low
.
Wi
nd
:
Wi
nd
i
s
t
h
e
fo
re
mo
st
e
n
v
i
r
on
me
nt
a
l
i
n
f
lu
e
n
c
e
t
h
a
t
di
st
u
r
b
s
t
h
e
U
A
V
beca
use
of
i
t
s
d
irec
t
i
on
of
f
low
and
spe
e
d.
W
in
d
m
a
y
g
i
ve
b
ene
fi
t
t
o
t
he
e
ner
g
y
co
nsum
p
t
i
o
n
s
o
r
g
i
v
e
bi
gge
r
resistance
t
o
the
move
me
nt
i
n o
t
her
scena
r
i
o
s [14].
Te
mpe
r
ature
:
T
he
s
ce
ner
i
es
o
f
t
e
mpe
r
at
ure
is
a
b
l
e
to
d
ist
u
rb
t
h
e
UAV’
s
b
a
tt
ery
p
r
o
v
is
io
n
as
i
t
i
s
in
t
e
rre
l
a
t
e
d t
o
dr
a
i
n
bat
ter
y
a
nd
its c
apa
b
il
i
t
y
[1
5].
vi
i
.
UAV
Fl
y
i
ng
S
p
e
e
d
an
d
Pa
yl
oa
d
Th
e
relati
v
e
a
n
d
rat
i
o
n
a
l
flyin
g
sp
eedin
ess
o
f
t
h
e
UAV
i
s
a
p
rec
ari
o
us
i
ssue
t
o
de
te
rmine
t
h
e
fue
l
con
s
um
pt
io
n. D
irec
t
i
o
n
o
f
t
h
e Wi
nd
s
pee
d
i
s
r
e
la
ted
w
i
t
h
the
fl
y
i
n
g
spee
d
bec
a
u
se w
i
n
d
di
r
e
c
t
i
o
n di
st
urbs t
he
fly
i
n
g
st
and
a
rd
o
f
t
h
e
UAV
,
e
i
t
h
er
p
osit
i
v
ely
o
r
n
eg
ati
v
e
l
y.
T
h
e
fl
y
i
n
g
posit
i
o
n
o
f
a
UAV
can
si
t
u
at
e
at
a
ny
sub
s
e
q
ue
nt
:
a
.
h
o
v
eri
n
g
an
d
b.
l
e
v
e
l
fl
i
g
h
t
,
cruis
i
n
g
o
r
h
o
riz
o
n
ta
l
mov
i
ng
a
l
so
c
.
vert
ica
l
m
o
v
i
ng
:
ve
rtica
l
take-
o
ff/
a
lti
t
u
de
a
d
j
us
tm
ent
/la
n
d
i
ng
a
lte
ra
t
i
on.
T
her
e
fore
,
t
h
e
fl
yi
ng
c
ond
it
io
n
of
t
h
e
UAV
mu
st
b
e
me
asure
d
a
lo
n
g
w
i
t
h
t
h
e
fl
y
i
n
g
spe
e
d
ine
ss
in
c
om
pu
ti
n
g
t
he
e
ne
rg
y
fee
d
in
g
[1
4].
Bes
i
des
t
h
a
t
,
the
r
e
late
d
mode
l
s
a
re
propos
e
d
i
n sec
tio
n 3
w
ith
r
ela
tiv
e
en
r
oute for t
h
e
se fl
i
g
ht statuses.
No
r
m
al
l
y
,
UAVs
car
ry
s
p
ecif
i
c
fo
rms
o
f
p
ay
lo
ad
s,
f
o
r
i
n
s
tan
c
e,
ca
me
ra
k
i
t
o
r
p
a
rc
el
s
.
E
f
f
ect
o
f
th
e
di
ssim
ila
r
ma
sse
s
o
f
pa
yloa
ds
m
i
g
ht
b
e
s
i
gnifi
can
t
w
h
e
n
d
er
ivi
n
g
t
he
m
ode
l
of
e
ne
rg
y
c
o
n
s
u
m
p
t
ion
[14,
15]
.
In aircr
aft en
gi
neer
ing,
i
t is re
c
og
n
i
ze
d
tha
t
t
he ene
rg
y
/
f
u
el
c
onsum
p
t
i
o
n i
s
subje
c
t
to c
e
rt
a
i
n fac
t
ors. P
e
r
hap
s
,
max
i
mu
m
fli
gh
t
ti
me
o
r
fli
gh
t
d
i
st
an
ce
o
f
UAV
may
b
e
c
o
n
st
rain
ed
b
y
ta
ke
off
to
ta
l
w
e
ig
ht,
o
v
e
r
w
e
ig
h
t
,
em
pty
w
e
i
g
h
t
a
nd
thru
st
t
o
t
h
e
w
e
i
g
h
t
r
a
t
io
[
1
6
],
p
a
y
loa
d
,
and
fuel
w
eight
[
17].
S
ince
the
UAV
’s
eng
i
nee
r
i
n
g
/
m
a
nu
fa
c
t
uri
n
g,
i
n
d
i
v
i
dua
l
ca
n
ge
t
e
q
u
i
vale
nt
p
ro
t
o
t
ype
s
i
n
te
n
d
e
d
f
or
fl
ig
ht
f
or
e
x
a
m
p
l
e
,
exi
s
ti
ng
/
o
b
t
a
i
na
ble
f
u
e
l
r
e
p
lic
as
f
or
m
ul
t
i
-
r
otor
h
e
l
ic
op
ter
s
[
18]
w
h
i
c
h
d
e
m
ons
trate
the
linea
r
es
tim
at
io
n
o
f
the e
n
er
gy
in
g
e
st
in
g is n
ot a
p
p
ro
priate
a
im
ed a
t
hu
ge
d
e
v
ia
tio
n
s of t
he
p
a
y
l
o
a
d
c
on
ve
ye
d
[1
5].
v
iii. C
o
m
put
at
i
ona
l com
p
lex
i
t
y
Th
is
i
s
a
me
t
r
ic
a
ssocia
t
e
d
w
it
h
com
puta
t
i
o
nal
per
f
orm
a
nc
e
of
a
n
a
l
g
o
r
i
t
h
m
.
I
t
i
s
i
m
p
o
r
t
a
n
t
t
h
a
t
t
h
e
com
p
u
t
a
t
i
o
na
l
c
o
mple
x
i
ty
o
f
eve
r
y
alg
o
ri
t
h
m
ne
eds
t
o
b
e
cons
id
e
re
d,
b
ec
au
se
c
omp
u
ta
t
i
o
n
a
l
t
i
m
e
c
a
uses
ene
r
g
y
c
o
n
s
u
m
p
t
i
on
[1
9].
ix
.
Sc
ala
b
i
l
ity
:
The
a
s
se
ssm
e
n
t
o
f
a
pa
th
p
la
nn
i
ng
a
l
gor
it
h
m
f
or
a
n
au
to
nomo
u
s
v
ehi
c
l
e
o
r
UAV
i
s
c
o
n
s
id
ered
a
s
scala
b
il
ity.
S
cala
b
il
ity
i
s
a
state
w
h
e
n
w
it
h
a
lar
g
er
n
e
t
w
o
rk,
t
he
p
e
rform
anc
e
o
f
an
a
l
gori
t
hm
d
e
c
li
nes.
H
e
nc
e,
a
w
el
l
performe
d
a
l
g
ori
t
hm
w
h
i
c
h
i
s
de
s
i
gne
d
f
o
r
tri
v
i
a
l
p
a
t
h
ne
tw
or
k
proba
b
l
y
w
o
n
'
t
be
a
p
p
ropr
iat
e
for
big
g
e
r
pa
t
h
netw
orks.
x
.
Q
uali
t
y o
f
th
e
be
st
p
a
th:
Th
is
m
e
t
r
i
c
i
s
u
ti
liz
ed t
o
c
o
m
p
ar
e
t
h
e
m
u
l
t
i
p
le
f
ine
s
t
pa
ths th
a
t
a
re
p
l
a
nne
d
and
c
o
mpu
t
e
d
by
a
l
t
e
re
d
heur
ist
i
c
s
a
n
d
s
up
p
o
rt
ive
t
o
s
imilar
m
e
tr
ics
(i.e
.
trave
l
t
ime
,
t
ra
v
e
l
di
st
ance
e
t
c
.)
w
it
h
th
e
ai
m
of
d
ecid
i
ng
w
h
ic
h a
l
gor
it
h
m
is m
a
nip
u
l
at
i
v
e
i
n
o
bta
i
n
i
n
g
the
n
ear
es
t answ
e
r
/clar
i
fic
a
tio
n
to
t
he i
dea
l
or
op
t
i
m
a
l pa
th.
3.
FLIGHT
C
O
S
T CALCULAT
ION M
E
THO
D
AND
A
NALYSIS
C
ons
ide
r
a
U
A
V
’
s
pat
h
a
s
dep
i
c
t
ed
i
n
F
i
gure
1.
T
he
p
ath
s
t
ar
t
s
at
S
a
nd
e
n
ds
a
t
G
t
hr
ou
gh
a
w
a
yp
oi
n
t
W
. Note tha
t, i
n the fi
gur
e,
ϴ
=
∠
i
s
180
°
w
h
i
ch
m
ean
s
n
o
UAV’s
h
e
ad
ing
ch
ang
e
t
hro
u
g
hou
t
the pa
th.
The
r
efore,
the
U
A
V
tra
verse
s
t
he p
a
t
h i
n
a
s
t
r
ai
gh
t l
ine
from
po
int
S
to
G
.
Th
e co
st
,
can
b
e
calcu
la
t
e
d u
s
ing
t
h
e fo
llow
i
n
g
(1)
D
D
1
s
i
n
18
0
θ
)
(1
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
P
o
w
Elec
&
D
r
i
S
y
st
I
S
S
N
:
2088-
86
94
Fl
i
g
h
t
cost
c
a
l
c
ul
a
tio
n for un
m
a
n
n
ed
a
i
r
v
e
h
ic
le b
a
se
d
on
pat
h l
e
n
g
t
h a
n
d
hea
d
i
n
g
(
San
joy
K
u
m
a
r D
e
bn
a
t
h)
38
5
F
i
gur
e
1.
U
A
V
pa
t
h
fr
om
s
ta
r
t
i
n
g
p
o
in
t
S
t
o
go
a
l
p
oi
nt
G
t
hr
ou
g
h
a
w
aypo
i
n
t
W
w
i
t
h
no
he
a
d
in
g
c
h
an
ge
The
e
qua
tio
n
im
plie
s
t
h
a
t
,
if
t
her
e
i
s
no
h
ea
d
i
n
g
a
ng
le
c
ha
n
g
e
o
n
t
h
e
p
a
t
h
towa
rds
t
h
e
go
al,
th
en
t
he
to
ta
l c
o
st
i
s
o
n
ly
t
he d
is
ta
nce
of
t
he pa
t
h.
F
i
gur
e
2
de
p
i
c
t
s
a
pat
h
,
w
h
i
c
h
st
a
r
ts
a
t
S
a
n
d
e
n
d
s
a
t
g
o
a
l
s
G
1
t
o
G
10
.
As
su
me
t
h
a
t
th
e
UAV
h
a
s
to
tr
a
v
er
se
t
he
p
at
h
a
n
d
a
f
ter
r
e
a
c
hi
n
g
a
t t
h
e w
a
y po
in
t
W
,
i
t
ch
a
n
g
e
s
it
s
he
ad
i
n
g
an
gl
e
t
o
ward
s
go
al
po
i
n
t
s
G
1
t
o
G
10
w
i
th
th
e
ang
les
o
f
ϴ
=
18
0
, 1
7
0
, 1
6
0
,
15
0
,
14
0,
1
3
0
,
120
, 1
1
0
,
100
a
nd
90
res
p
ectiv
e
l
y
.
I
t
c
a
n
b
e
i
n
t
e
r
p
r
e
t
e
d
t
h
a
t
f
o
r
a
n
a
n
g
l
e
o
f
1
7
0
,
t
h
e
U
A
V
h
a
s
t
o
m
a
k
e
a
1
0
h
eadin
g
ch
a
n
g
e
.
T
h
i
s
r
e
sults
i
n
the
minim
u
m
U
A
V
s
pe
ed
c
ha
n
g
e
t
o
cate
r
t
he
t
ur
n.
A
f
t
e
r
pa
ssi
ng
W
,
the
UA
V’s
speed
w
il
l
be
r
e
stor
ed
t
o
the
nor
ma
l
o
n
e.
T
he
s
l
i
g
h
t
c
ha
n
g
e
i
n
t
he
U
A
V
s
pee
d
(
s
l
o
w
s
dow
n
an
d
spe
e
d
s
u
p
)
w
i
l
l
r
e
s
ult
i
n
sm
all
ene
r
g
y
l
oss.
F
or
t
he
w
orst-c
ase
scena
r
io,
where
the
h
e
ad
i
ng
c
h
an
g
e
i
s
9
0
,
th
e
UAV
h
a
s
to
i
n
s
tantly
r
e
duce
i
t
s
s
p
ee
d
a
n
d
a
g
a
i
n
r
a
pi
d
l
y
i
n
cr
e
a
se
i
t
s
s
pee
d
t
o
t
h
e
no
r
m
a
l
o
n
e
a
f
t
e
r
p
a
s
s
i
n
g
W
.
This
cau
se
s
the
UAV
to c
o
n
s
u
me
cons
idera
b
l
y
m
ore
ener
gy com
p
ar
ed to
the
for
m
e
r
sc
e
n
ar
i
o
.
F
i
g
u
r
e
2
.
U
A
V
p
a
t
h
w
i
t
h
d
if
fe
r
e
nt
g
oal
co
ns
ide
r
i
ng
d
i
f
f
e
r
e
n
t
an
gl
e
Ther
ef
or
e
,
f
r
o
m
(
1
)
a
nd
r
e
fer
r
i
n
g
t
o
F
i
g
u
r
e
2
,
c
a
n
be
c
onst
r
uc
t
ed
as
(2
)
Cost
=
d
+
d
=
d
+
d
1
s
in
1
80
θ
(
2
)
The
calc
u
late
d
costs
from
S
t
o
b
e
l
i
s
t
e
d
i
n
Ta
b
l
e
1
c
onsi
d
er
i
n
g
F
i
gur
e
2
and
a
s
sum
i
n
g
tha
t
t
h
e
d
i
st
an
c
e
b
et
wee
n
S
a
nd
W
is 7m an
d
W
t
o
G
i
is
2m
.
I
n
T
ab
le
1
,
i
t
i
s
c
l
e
a
r
l
y
o
b
ser
v
e
d
t
ha
t
the
gr
adua
l
i
n
cr
em
ent
i
n
th
e
a
ngl
es
c
au
se
s
t
h
e
g
r
a
d
u
a
l
ra
i
s
e
i
n
e
n
er
g
y
c
ons
umpt
i
on.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
0
8
8
-
86
94
I
nt
J
P
o
w
E
l
e
c
&
D
r
i
S
yst
V
o
l.
11,
N
o.
1
,
Mar
202
0
:
382
–
38
9
38
6
Ta
bl
e
1
.
En
e
r
gy
l
os
s
wi
t
h
d
i
ffe
r
e
n
t
ang
l
e
Goal
18
0
°
9.
00
17
0
°
9.
35
16
0
°
9.
68
15
0
°
10.
00
14
0
°
10.
29
13
0
°
10.
53
12
0
°
10.
73
11
0
°
10.
88
10
0
°
10.
96
90
°
11.
00
4.
S
I
MULAT
I
ON R
E
S
UL
T A
ND
DISCU
SSION
The
pr
op
ose
d
e
qua
t
i
o
n
i
n
t
h
e
pr
ev
io
u
s
s
ec
t
i
on
is
a
p
p
l
i
e
d
t
o
f
i
n
d
th
e
cos
t
o
f
a
r
a
n
d
o
m
l
y
ge
ner
a
te
d
pa
th
s
h
o
w
n
i
n
F
i
g
u
r
e
3
.
The
U
A
V
h
a
s
t
o
t
r
a
v
er
se
t
he
p
a
t
h
fr
om
t
h
e
s
t
a
rt
in
g
poi
nt
S
t
o
g
o
a
l
poi
nt
G
w
i
t
h
m
u
lti
pl
e
head
i
ng
c
h
a
n
ges.
H
er
e,
t
he
obsta
c
l
e
s
a
r
e
not
s
how
n.
F
i
g
u
r
e
3
. Th
e
UAV h
a
s
t
o
t
rav
e
rse
t
h
e p
a
th
fro
m
S
t
o
G
poi
nt
w
i
t
h
m
u
l
t
i
p
l
e
h
e
a
di
n
g
c
ha
n
g
es
The
to
ta
l
l
e
ng
th
o
f
t
h
e
pat
h
w
it
ho
ut
c
ons
i
d
er
in
g
t
h
e
hea
d
ing
c
h
a
n
ges
is
25m
.
B
u
t,
onc
e
t
h
e
c
h
an
ge
s
in t
he
hea
d
i
n
g
a
ng
le
a
re
take
n
i
nto
ac
co
un
t t
h
en t
o
t
al c
ost
i
s
34.
33m
.
G
e
ne
r
a
ll
y,
m
ulti
p
l
e
hea
d
in
g
a
n
g
l
e
c
h
an
ge
s
o
c
cur
due
t
o
t
h
e
incr
e
a
se
i
n
t
h
e
num
ber
o
f
t
ur
ns
w
i
t
h
the
incr
eas
in
g
n
u
m
ber
of
obsta
c
l
es
i
n
a
U
A
V
pat
h
.
I
n
a
s
tr
a
i
gh
t
pa
t
h,
U
A
V
m
a
i
nta
i
n
s
a
s
t
e
ady
s
p
ee
d.
I
n
a
path
wit
h
p
ie
ce-
wi
s
e
l
i
n
ear
s
egm
e
nt
s
whi
c
h
a
r
e
no
t
par
a
lle
l,
t
h
e
UAV
h
a
s
t
o
c
h
a
n
g
e
i
t
s
h
e
a
d
i
n
g
a
n
g
l
e
n
e
a
r
t
h
e
w
a
yp
oin
t
s
t
o
a
vo
i
d
o
bs
tacle
s
.
Cha
n
gin
g
t
he
h
ea
d
i
ng
a
n
g
l
e
w
i
l
l
r
esul
t
in
r
educ
e
d
s
pee
d
(
dec
e
ler
a
tio
n)
.
A
f
t
e
r
p
a
s
s
ing
the
way
point,
th
e
UAV
may
star
t
to
a
ccelerate
a
g
ain
.
T
h
is
d
ece
ler
a
ti
o
n
a
nd
ac
ce
le
rati
on
w
ill
lea
d
t
o
m
o
r
e
e
ne
r
gy
c
onsum
p
t
ion
[2
0]
.
Fu
rt
h
e
rmo
r
e
,
T
a
b
l
e
1
c
l
e
arly
d
emon
st
rat
e
s
th
a
t
t
h
e
g
reat
e
r
h
ea
d
in
g
c
h
a
nge
c
a
u
ses
ad
dit
i
o
n
a
l
en
e
r
gy
c
o
n
s
um
p
t
i
o
n
and
i
n
cr
ease
s
t
he
p
a
t
h
co
s
t
.
F
i
gur
e
3
a
l
so
ill
us
tr
a
tes
the
sam
e
t
he
or
y
of
m
or
e
ene
r
g
y
c
o
n
s
um
p
t
i
o
n
w
ith
i
n
c
r
e
asin
g
hea
d
i
ng
an
g
l
e
c
h
an
ge
o
f
a
UA
V
.
5.
FUTURE WORK
I
n
[
9,
21]
,
it
is
s
h
o
w
n
t
ha
t
fo
r
op
tima
l
e
ner
gy
e
f
f
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c
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t
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p
l
a
n
n
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ng
for
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a
ut
o
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ve
hi
c
l
e
or
unm
an
ne
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air
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i
c
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p
a
r
ti
c
u
l
a
r
l
y
tw
o
a
l
gor
i
t
hm
s
ar
e
b
e
s
t
f
it.
T
hey
a
r
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visib
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lit
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gr
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(
V
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ial
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h
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go
rit
h
m.
B
ot
h
me
th
od
s
are
v
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ry
g
ood
i
n
ter
m
s
of
o
ptim
izat
i
on
a
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d
c
o
mplete
ness
q
u
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li
t
y
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I
f
w
e
a
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ply
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t
h
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r
gy
sa
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pos
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x
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us
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n
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h
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s
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o
T
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d
u
e
t
o
t
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“
I
n
t
e
roper
a
bi
lit
y”
w
hic
h
c
a
n
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e
con
s
i
d
ere
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i
n
the
a
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t
a
g
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o
f
a
pr
ojec
t
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ma
t
i
on
tra
n
s
p
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r
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”.
I
n
add
i
t
i
o
n
,
the
des
i
r
e
d
ou
tc
ome
can
a
l
s
o
be
o
b
t
a
i
ne
d
w
i
t
h
t
he
s
ele
c
t
ed
a
lg
ori
t
hm
b
y
im
p
l
e
me
n
tin
g
the
esse
nt
i
a
l
ke
y
tec
h
nol
og
i
e
s
for
I
n
d
u
s
t
r
y
4
.
0
t
r
a
n
s
f
o
r
m
a
t
i
o
n
s
u
c
h
a
s
a
d
a
p
t
i
v
e
r
o
b
o
t
i
c
s
p
a
r
t
l
y
o
r
f
u
l
l
y
,
cl
ou
d
sys
t
em
s,
c
ybe
r
sec
u
rity,
machi
n
e
lear
n
i
n
g
,
ar
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
enc
e
,
and
IoT [22-25].
6.
CONCL
U
S
ION
Thi
s
s
t
udy
i
ntro
du
c
e
d
a
n
e
w
t
e
c
hni
qu
e
to
c
a
l
c
u
l
a
t
e
t
he
f
l
i
gh
t
c
o
s
t
o
f
a
n
un
ma
nn
ed
a
i
r
v
eh
i
c
le
con
s
i
d
eri
ng
it
s
head
in
g
an
g
l
e
chan
ge
s
for
a
n
o
ptim
al
e
ne
rgy
e
f
f
icie
n
t
p
a
t
h
pla
n
ni
n
g
a
ppr
oac
h
.
Besi
de
s
tha
t
,
so
me
o
t
h
er
f
act
o
r
s
a
r
e
al
so
d
i
s
cu
s
s
e
d
w
hi
c
h
i
nfl
u
e
n
c
e
d
t
h
e
en
e
r
g
y
c
ons
um
pti
on.
T
h
e
n
ew
m
eth
o
d
exa
m
i
n
e
d
the
ge
ner
a
l
ch
ar
acter
ist
i
cs
o
f
the
e
n
e
r
g
y
i
n
g
e
s
ti
n
g
o
r
co
n
s
ump
t
i
o
n
f
o
r
a
U
A
V
’
s
p
a
t
h
pla
n
ni
n
g
.
The
re
sult
rev
e
al
ed
t
h
a
t
t
h
e
en
ergy
c
on
su
mp
t
i
o
n
o
f
a
UAV
i
n
creased
du
e
t
o
t
h
e
i
n
cre
a
sing
n
u
m
b
er
o
f
hea
d
ing
a
n
g
l
es
a
s
a
re
sul
t
o
f
t
h
e
growi
ng
n
u
m
b
er
o
f
o
b
s
t
acl
es.
The
the
o
re
tica
l
a
n
d
m
a
th
em
atica
l
a
na
ly
sis
a
nd
outc
o
m
e
s
vi
a
si
m
u
lat
i
on
pro
v
ed
t
he
e
ff
i
c
ac
y
of
t
his
me
t
h
od.
T
he
s
ig
n
i
fi
canc
e
o
f
th
e
ste
a
l
thy
p
a
th
i
s
imme
n
s
e
i
n
t
e
r
ms
o
f
sav
i
n
g
ene
rg
y i
n
U
A
V
pa
t
h
p
l
a
n
n
i
ng.
ACKNOW
LEDG
E
MEN
T
S
The
a
u
t
h
ors
w
ould
l
i
k
e
to
g
ive
spec
i
a
l
tha
nks
t
o
Mi
n
i
s
t
r
y
o
f
H
i
ghe
r
Educa
tio
n
Ma
lays
ia
a
n
d
U
n
i
v
ersi
ti
Tu
n
H
u
sse
i
n
O
nn
Ma
lays
ia
a
s
s
o
c
ia
t
e
w
ith
R
e
s
e
a
r
c
h
M
a
n
ag
eme
n
t
Ce
nt
e
r
,
fo
r
t
h
e
re
se
arc
h
f
und
sup
por
t
u
nder
TIER-1 V
O
T
H
13
1.
REFE
RENCES
[1]
Yang
L
,
Q
i
J
,
S
o
n
g
D
,
X
i
ao
J
.,
Han
J.,
X
i
a
Y.
,
"
S
urv
e
y
of
r
o
b
o
t
3
D
p
a
th
p
la
n
n
i
n
g
a
lg
or
i
t
h
ms
,"
J
o
urna
l o
f
C
o
n
t
r
o
l
Sci
e
nce a
n
d
En
g
i
n
eeri
n
g
,
Vo
l. 1
,
No
. 5
, Mar 2
01
6
[2]
Wa
ha
rte
,
S
on
ia
,
a
n
d
Niki
T
r
i
g
o
n
i.
"
Su
pp
ort
i
n
g
s
e
a
r
c
h
a
nd
r
esc
u
e
o
perati
ons
with
UAVs,"
Em
ergi
ng
S
ecurit
y
Tech
nol
og
ies
(ES
T
),
20
10
In
t
e
rnat
ion
a
l Con
f
er
en
ce o
n
.
IEEE
, 2
01
0.
[3]
Tri
p
i
c
chio,
Paol
o,
M
assi
mo
S
a
tle
r,
G
iaco
m
o
D
ab
isi
a
s,
E
m
a
nuel
e
R
u
f
f
a
ld
i
,
a
nd
C
arl
o
A
l
b
erto
A
vi
zzano
.
"
To
ward
s
sm
art
f
a
rm
in
g
and
su
st
a
i
n
a
ble
agri
culture
w
ith
d
r
ones
.
"
In
In
tell
ig
en
t
E
n
viron
m
en
ts (
I
E)
,
2015
In
ter
n
a
t
io
n
a
l
Con
f
eren
ce on
, IE
EE
, p
p.
14
0
-1
4
3
, 20
1
5
.
[4]
"UAS t
ra
ffic m
a
nagem
e
nt
," [Onli
ne] Avail
a
bl
e
h
ttp://
www.utm.ar
c
.na
s
a
.
go
v/ut
m2
01
5. sh
t
m
l
.En
g
in
e
e
r
in
g 2
0
1
6
[5]
Ah
m
e
d
,
S
h
a
im
a
a
,
Am
r
M
o
h
a
med,
K
hal
e
d
Harras,
M
oham
e
d
Kh
ol
ie
f
,
a
n
d
S
a
le
h
M
e
sb
ah.
"E
ne
rgy
ef
fici
ent
path
pl
ann
i
ng
t
echn
i
q
u
es
f
or
U
A
V
-b
ased
s
yst
e
ms
w
ith
s
pace
discreti
za
tion.
"
In
Wi
rel
e
ss Commu
ni
cati
on
s and
Netwo
r
kin
g
Co
n
f
erence (
W
CNC), 20
16
IEE
E
,
p
p
.
1
-6. I
EEE, 2
01
6
.
[6]
Gi
esbrech
t,
J
.
Gl
ob
al
p
at
h
plann
i
n
g
f
or
u
nm
ann
e
d
g
r
oun
d
v
e
hi
cle
s.
N
o.
D
RDC-TM
-2
00
4-27
2,
"
D
e
fe
n
c
e
re
se
a
r
ch
an
d
devel
opm
en
t
s
u
f
f
i
e
ld (
a
lberta)
,
"
2
00
4,
M
.
You
n
g
,
T
he
T
ec
h
n
i
cal
W
riter’s
H
an
db
oo
k.
M
il
l
Val
l
ey
,
CA:
Un
iv
e
r
sit
y
S
ci
en
ce,
198
9.
[7]
LaValle
,
S
t
even
M
., "
Plan
n
i
ng
al
go
rithms
,"
C
am
bridg
e
un
i
v
e
rs
ity
p
ress, 2
00
6
.
[8]
Ma
se
hia
n
,
E
l
l
ip
s,
a
nd
D
a
v
ou
d
Se
digh
iz
a
d
e
h
.
"
C
la
ssic
a
n
d
h
e
ur
is
t
ic
a
p
p
roach
es
i
n
ro
bot
m
o
t
io
n
plann
i
n
g
-a
chro
no
log
i
cal
re
v
i
e
w,"
W
o
r
l
d
A
c
ad
emy o
f
S
c
ience
,
En
g
i
neeri
ng a
n
d
Tech
no
lo
gy
,
vo
l
.
29
,
No
.
1
,
p
p
.1
01
-1
06
,
2
0
0
7
.
[9]
Deb
n
ath
,
S
an
jo
y
K
u
m
a
r,
R
o
s
li
O
m
a
r,
a
nd
No
r
Ba
dari
yah
Ab
du
l
Lati
p
.
"
A
re
vie
w
o
n
e
n
e
r
gy
e
ffic
ie
nt
p
a
t
h
p
l
a
n
ning
alg
o
rithms
f
or
unm
an
ned
air
v
e
hi
cles,
"
I
n
Com
p
u
t
atio
nal Scien
ce an
d T
e
c
h
nol
og
y
,
p
p
.
5
2
3
-5
32
.
Spring
e
r
,
Sing
a
p
ore
, 20
1
9
.
[10]
Om
ar,
Ro
s
l
i
bin,
"
P
a
t
h
p
l
an
n
i
n
g
f
o
r
u
n
m
ann
ed aer
i
a
l
vehi
c
les
u
s
i
ng v
i
si
bilit
y
lin
e-ba
sed m
e
th
ods
,"
P
hD
d
i
s
s.,
U
n
i
v
e
r
s
i
ty
o
f
Le
ic
e
s
te
r
,
2
01
2
.
[11]
Yu
,
V.
F.
,
Li
n,
S
.
-
W.
,
"
S
o
l
ving
t
h
e
l
o
cati
on-ro
utin
g
p
r
obl
em
w
it
h
simu
l
t
a
n
e
o
u
s
p
i
c
ku
p
a
n
d
de
liv
e
ry
b
y
sim
u
la
te
d
ann
ealin
g,
"
Int.
J. Prod.
R
e
s
, vo
l
54
, pp
.
1
-2
4
, 20
1
5
.
[12]
Qi
an,
Z.
,
W
a
ng,
J
.
,
W
a
n
g
,
G.
,
"Rou
te
p
lan
n
i
n
g
of
U
A
V
b
ased
o
n
i
m
p
ro
ved
ant
co
l
o
n
y
a
lg
orit
h
m
,"
pp
.
1
421
-14
2
6
, 2
015
[13]
S
a
rıçiçek
,
İ.
,
Akkuş
,
Y
.
,
"Un
m
a
n
ned
a
e
rial
v
eh
icle
h
ub
-lo
catio
n
a
n
d
r
o
u
t
i
n
g
f
or
m
o
n
ito
ring
g
eograp
hi
c
bo
rders,
"
Appl. Math.
M
o
del
,
v
o
l
.
3
9
,
p
p
.
39
39
-3
95
3,
2015.
[14]
Tsen
g
,
C
-.M
.,
C
h
au
,
C-.K.,
El
b
a
ssion
i
,
K.
,
Kho
n
ji,
M
.
,
"
Au
t
o
n
o
m
ou
s
rech
arg
i
n
g
a
n
d
f
l
i
g
h
t
m
i
s
s
io
n
plan
ni
ng
f
or
bat
t
ery-o
p
erat
ed
a
u
t
o
nom
o
u
s
drones
,
p
p
.
1
-10,
2017
.
[15]
Do
rli
ng,
K
.,
H
e
i
nri
c
hs,
J.,
M
e
ssier,
G
.
G
.
,
M
a
gierow
ski
,
S
.
,
"
V
e
hicl
e
rou
t
i
ng
pro
b
lem
s
f
or
d
rone
d
el
iv
ery
,
"
IE
EE
Tran
s. S
y
st.
Man
Cy
be
rn
.
S
y
st
.
,
v
ol.
4
7
, p
p.
1-1
6
,
2
01
6.
[16]
S
h
et
ty,
V
.
K.,
Sudi
t,
M
.,
N
agi,
R
.
,
"P
ri
ority
-based
a
ssi
gn
m
e
n
t
a
n
d
rou
tin
g
of
a
fl
eet
o
f
un
m
a
nned
com
b
at
aeri
a
l
veh
i
cles
,"
C
o
m
p
u
t
. Oper
.
R
e
s
.,
v
ol.
35
, p
p.
1
81
3-
1
8
2
8
, 2
00
8.
[17]
Zhan
g,
J
.
,
J
ia,
L
.
,
N
i
u,
S
.,
et a
l
.,
"A
s
pa
ce-ti
m
e
n
etw
o
rk-b
ased
m
o
d
eli
n
g
fram
e
w
o
rk
f
o
r
d
yn
amic
u
n
m
an
ned
ae
r
i
al
veh
i
cle
routin
g in
t
ra
f
fi
c i
n
ci
d
e
nt
m
onit
o
rin
g
a
p
p
licat
ions,
"
S
e
ns
ors
(S
w
i
t
z
e
rl
an
d),
v
o
l. 1
5,
pp
.
13
8
7
4
-1
3
8
9
8
, 20
1
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N: 2
0
8
8
-
86
94
I
nt
J
P
o
w
E
l
e
c
&
D
r
i
S
yst
V
o
l.
11,
N
o.
1
,
Mar
202
0
:
382
–
38
9
38
8
[18]
L
e
i
s
h
m
an,
D
.
S.
,
(
E
ng
.
PDFRASJG) P
r
inc
i
ples of
Hel
i
copter A
e
r
o
dynamics
,
20
06
.
[19]
L
a
ti
p,
N
or
B
ad
ariy
ah
A
bd
ul,
Ro
s
l
i
Om
ar,
and
S
a
nj
oy
Ku
mar
Debn
at
h
,
"
Op
timal
p
ath
pl
anni
ng
u
s
i
n
g
e
q
u
ilat
e
ral
s
p
aces
o
rien
ted
v
i
sib
i
lit
y
grap
h
m
e
th
od
,"
Inter
n
a
t
i
o
n
a
l
Jo
ur
nal of
El
ectri
cal
and
Com
p
u
t
er E
ngin
eerin
g (
I
JE
CE)
,
v
o
l
.
7
,
No
.
6
,
p
p.
3
04
6-3
051
,
2
017.
[20]
Bi
nitha,
S
.
,
an
d
S
.
S
iva
S
a
t
h
y
a
,
"A
s
urv
e
y
o
f
b
io
i
nspired
op
ti
mizati
o
n
alg
o
rithms,"
Int
e
rn
ational
jo
u
r
na
l of s
o
ft
co
mp
uti
ng an
d engi
neer
in
g
,
v
o
l
. 2
,
N
o.
2
,
p
p
.
137-15
1,
2
0
12.
[21]
D
e
bn
ath,
S
an
joy
Ku
mar,
R
o
s
l
i
O
m
a
r,
a
nd
N
or
B
adari
y
ah
A
bd
ul
L
ati
p.
"
Co
m
p
ari
s
on
o
f
d
i
ff
ere
n
t
con
f
ig
uration
s
p
ace
r
e
p
r
esent
a
ti
ons
f
o
r
p
at
h plan
ni
ng
u
n
d
er co
m
bi
na
t
o
rial
m
et
ho
d,"
Ind
o
n
e
si
an Jou
r
na
l of
El
e
c
tr
ica
l
E
ngi
neerin
g
an
d Co
mp
u
t
e
r
S
c
ie
nc
e
, vo
l
. 1
, N
o. 1,
p
p
.
40
1-4
0
8
, 20
1
9
.
[22]
H
e
rman
n
M
,
P
e
n
t
e
k
T,
O
tto
B
.
,
"Des
ig
n
pri
n
ci
p
l
es
f
or
i
nd
u
s
tri
e
4
.
0
s
c
en
ario
s,"
In
S
ys
te
m
Sci
e
nces
(
H
I
CSS
)
,
49
th
Hawaii In
tern
a
t
ion
a
l
Conferen
ce. IE
EE
,
p
p
.
3
928-39
37
,
2
016
.
[23]
S
a
rv
ari
P
A
,
Us
tu
nd
ag
A
,
Cevi
kcan
E
,
Kay
a
I
,
Cebi
S
.
,
"
T
echno
lo
g
y
roa
d
ma
p
for
in
du
stry
4
.0
:
Ma
na
g
i
n
g
Th
e
Dig
ita
l
Tra
n
s
f
orma
t
i
on
,
"
Sp
ring
e
r
,
C
ha
m
,
p
p
.
9
5
-
10
3,
201
8.
[24]
Sa
ntu
c
c
i
,
Gé
ra
ld
.
"
T
he
i
n
t
e
r
ne
t
o
f
t
h
i
ng
s:
B
e
t
we
e
n
t
he
r
e
v
olut
i
on
o
f
th
e
intern
et
a
n
d
t
he me
t
am
orpho
sis
of
o
b
j
ects,"
V
i
s
i
on a
nd
Challe
n
g
es
fo
r
Realisin
g t
h
e Inter
n
et o
f
T
h
i
ngs
,
p
p
. 1
1-
2
4
, 2
01
0.
[25]
M
a
t
t
ern,
F
ri
e
d
em
ann
,
a
n
d
C
hrist
i
an
F
lo
erkem
e
ie
r,
"
F
r
om
t
he
i
nte
rn
et
o
f
co
m
p
u
t
ers
t
o
t
h
e
i
ntern
e
t
of
t
h
i
ngs,
"
F
ro
m
act
iv
e
dat
a
m
anagem
en
t t
o
ev
e
nt
-bas
ed s
yst
e
m
s
an
d
m
o
r
e,
S
p
ringer
,
Berli
n
,
H
e
id
e
l
b
e
rg,
p
p
.
242
-2
5
9
,
20
10.
BIOGRAPHI
E
S
OF
AUT
HORS
San
j
o
y
K
u
m
ar
D
ebn
a
th
i
s
a
P
h
D
scho
lar
i
n
F
acult
y
o
f
E
lect
rical
&
El
ectro
n
i
c
En
gin
eerin
g
in
t
he
Uni
v
ersiti
T
u
n
H
u
ss
ein
Onn
Malaysia
(
UTHM).
H
e
received
hi
s
Mas
ters
o
f
Engineering
f
r
om
Uni
v
ersiti
Tekn
ol
ogi
Malays
i
a
i
n
2014.
H
e
joi
n
ed
a
r
esea
rch
on
“
O
pti
m
a
l
E
nergy
Ef
ficient
Path
Pl
ann
i
n
g
f
o
r
a
n
U
n
m
a
nn
ed
A
ir
V
ehi
c
le
(
UA
V)
i
n
O
b
stacl
e-Ri
c
h
E
nv
iron
me
n
t
”
in
2
01
6
a
t
U
T
H
M
und
er
t
he
O
ffic
e
o
f
Research
,
Inn
o
v
a
ti
on,
C
o
m
merci
a
li
zati
o
n,
a
n
d
Co
ns
ultan
c
y
Man
a
g
e
m
e
nt
c
e
n
t
er.H
e
is
a
“
Grad
uat
e
E
ng
ineer”
f
r
om
B
oard
o
f
E
ngin
e
ers
Mala
y
s
i
a
a
lso
a
“Grad
u
at
e
M
e
mber”
from Inst
i
t
ute of Engi
n
eers Mala
ys
ia as w
e
ll
IEEE M
alay
si
an s
ec
tion
resp
e
ct
iv
ely.
D
r
.
R
o
s
l
i
O
m
a
r
c
u
r
r
e
n
t
l
y
i
s
a
n
A
s
s
o
c
i
a
t
e
P
r
o
f
e
s
s
o
r
a
n
d
D
e
a
n
a
t
t
he
F
acul
t
y
o
f
E
lectri
cal
a
n
d
Elect
ronic
En
gi
n
eerin
g,
U
ni
versi
t
i
Tun
Huss
e
i
n
Onn
M
a
l
a
ys
ia.
He
r
ecei
ved
h
i
s
P
h
D
in
e
ng
ineeri
n
g
from
Un
iversity
o
f
Le
i
cester,
U
ni
te
d
King
do
m
in
2
01
2.
H
e
is
h
ig
h
l
y
m
o
tiv
a
t
ed
acad
em
i
c
ian
with
mo
re
t
han
1
5
y
ears
of
t
each
ing
and
resear
ch
e
x
p
erien
c
e.
H
is
r
es
earch
i
nt
ere
s
t
s
a
re
i
n
ro
boti
c
e
n
gi
neeri
ng,
a
uton
om
ou
s
system
s
and
syst
e
m
id
e
nt
ificat
io
n
.
Dr.
Babul
S
a
l
am
K
S
M
K
ad
er
I
brah
im
(
P
h
D
from
S
h
e
ffi
eld
Un
iversit
y
,
U
nited
Ki
ngd
o
m
)
i
s
a
n
Assistan
t
P
r
of
e
s
s
o
r
i
n
A
utom
at
io
n
and
Rob
o
ti
c
of
S
cho
o
l
o
f
M
ech
an
ical,
Aero
sp
ace
a
n
d
Aut
o
m
o
ti
ve,
Co
v
e
nt
ry
U
n
i
v
e
rsity,
U
n
i
t
ed
K
in
gdom
.
P
r
io
r
t
o
t
his
app
o
in
tm
en
t,
h
e
w
a
s
an
A
sso
cia
t
e
prof
es
so
r
in
D
e
p
artm
en
t
of
M
e
c
ha
t
r
onic
a
nd
R
obotic
E
ng
ineering
at
U
niv
e
rsi
t
y
Tu
n
H
u
ssei
n
O
nn
M
a
la
y
s
i
a
,
J
o
h
o
r
,
M
a
l
a
ys
ia
.
He
i
s
hi
gh
ly
m
o
t
iv
a
t
e
d
a
ca
de
mi
c
wi
th
s
i
gnificant
e
x
pert
i
s
e
in
t
he
f
ield
o
f
mech
atro
nics
w
i
t
h
sp
ecial
a
dheren
c
e
to
r
ob
otics
an
d
co
nt
rol
sy
s
te
m
s
w
ith
1
0
years
teachi
n
g
e
x
peri
enc
e
c
o
m
bi
ned
with
c
ou
rse
w
o
rk
a
nd
r
es
earc
h
b
ackg
r
o
u
n
d
.
H
e
h
a
s
pu
blish
e
d
mo
re
t
han
80
techn
i
cal
p
ap
e
r
s
in
j
o
u
rn
als
and
c
o
nf
eren
ce
p
ro
ceed
in
gs
i
n
thes
e
f
i
el
d
s
.
Dr.
Ib
rahi
m
is
a
C
hartered
Eng
i
n
eer
o
f
In
s
t
itutio
n
o
f
E
ng
in
e
e
ring
a
n
d
T
echn
o
l
ogy
(IET)
U
K,
P
rof
e
ss
io
na
l
Engi
neer
o
f
Bo
ard
o
f
Eng
i
n
eers
M
a
l
a
ys
ia
a
n
d
m
emb
e
r
of
I
EEE
.
H
is
r
esearch
i
n
t
eres
ts
i
n
c
lu
de
e
l
ectri
c
veh
i
cl
e
,
mech
atro
nics
,
nonl
in
ear
c
on
tro
l
a
nd
m
od
elli
ng,
r
ehab
il
it
ati
on
r
obo
ti
cs
a
n
d
c
on
tro
l
i
n
biomed
ic
al
a
p
pl
icat
ion.
Su
sam
a
B
agch
i
o
b
tai
n
ed
h
er
M
S
c
.
in
M
o
d
ern
Co
mm
un
icati
o
n
Techn
o
l
ogies
w
i
t
h
B
u
s
ines
s
Man
a
gem
e
nt
from
t
h
e
Univ
ersit
y
o
f
S
u
ssex
,
U
K
af
ter
com
p
l
e
ti
ng
t
h
e
B
a
c
h
e
l
or
o
f
En
gine
e
r
in
g
fro
m
the
U
n
i
v
ersi
ty
o
f
Burd
wan
,
W
es
t
Beng
al,
In
dia.
S
he
i
s
a
Do
cto
r
a
l
f
e
l
l
ow
a
t
the
Universiti
Tun
Hus
s
ei
n
O
n
n
Malay
s
ia
u
nd
er
t
he
F
acul
t
y
o
f
E
lect
rical
a
n
d
E
le
ct
r
on
ic
E
ngineeri
n
g
.
S
he
a
l
r
eady
gain
ed
8
y
e
a
rs
o
f
exp
e
rien
ce
i
n
corp
orat
e
(
e
ng
ineeri
n
g
m
a
nag
e
me
n
t
)
in
d
i
f
f
e
re
nt
s
ect
ors.
S
he
i
s
a
“G
radu
ate
Engineer”
f
r
o
m
B
oard
o
f
E
ngi
neers
Mal
a
ysi
a
(
BE
M
)
a
nd
“
G
radu
ate
M
e
m
b
er”
o
f
I
ns
it
u
t
e
of
Electri
cal & Elect
ro
n
i
cs
E
n
g
ineers (IE
EE
).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
P
o
w
Elec
&
D
r
i
S
y
st
I
S
S
N
:
2088-
86
94
Fl
i
g
h
t
cost
c
a
l
c
ul
a
tio
n for un
m
a
n
n
ed
a
i
r
v
e
h
ic
le b
a
se
d
on
pat
h l
e
n
g
t
h a
n
d
hea
d
i
n
g
(
San
joy
K
u
m
a
r D
e
bn
a
t
h)
38
9
Eli
a
N
adi
r
a
Sabudi
n
is
a
D
octoral
f
e
ll
ow
a
t
t
h
e
Uni
v
ersiti
Tun
Hu
ssei
n
O
n
n
M
alay
sia
un
der
th
e
Facu
lt
y
of
E
l
ectri
ca
l
and
El
ect
ro
ni
c
En
gin
eering.
S
h
e
r
eceiv
e
d
h
e
r
M
a
ster
o
f
En
gi
neerin
g
from
Uni
v
ersiti
Tun
Hussei
n
Onn
M
a
l
a
ysia
i
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15
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h
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in
m
echatro
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neeri
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g
at
t
he
Sch
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f
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ech
ani
c
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n
g
i
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eeri
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g,
Nort
hw
estern
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o
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yt
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niv
e
rsity,
Xi
’an,
C
hi
na.
His
cu
rren
t
resear
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eres
ts
i
n
dy
nami
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sy
ste
m
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nt
ific
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, rob
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od
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l
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g,
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nd
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on
tro
l
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