Drones,
Год журнала:
2023,
Номер
7(9), С. 544 - 544
Опубликована: Авг. 22, 2023
Unmanned
aerial
vehicles
(UAVs)
are
extensively
employed
for
urban
image
captures
and
the
reconstruction
of
large-scale
3D
models
due
to
their
affordability
versatility.
However,
most
commercial
flight
software
lack
support
adaptive
capture
multi-view
images.
Furthermore,
limited
performance
battery
capacity
a
single
UAV
hinder
efficient
capturing
scenes.
To
address
these
challenges,
this
paper
presents
novel
method
multi-UAV
continuous
trajectory
planning
aimed
at
reconstructions
scene.
Our
primary
contribution
lies
in
development
path
framework
rooted
task
search
principles.
Within
framework,
we
initially
ascertain
optimal
locations
images
by
assessing
scene
reconstructability,
thereby
enhancing
overall
quality
reconstructions.
curtail
energy
costs
trajectories
allocating
sequences,
characterized
minimal
corners
lengths,
among
multiple
UAVs.
Ultimately,
integrate
considerations
costs,
safety,
reconstructability
into
unified
optimization
process,
facilitating
paths
Empirical
evaluations
demonstrate
efficacy
our
approach
collaborative
full-scene
UAVs,
achieving
low
while
attaining
high-quality
Intelligent Decision Technologies,
Год журнала:
2024,
Номер
18(2), С. 919 - 934
Опубликована: Май 24, 2024
Unmanned
Ariel
Vehicles
(UAVs)
are
interconnected
to
perform
specific
tasks
through
self-routing
and
air-borne
communications.
The
problem
of
automated
navigation
adaptive
grouping
the
vehicles
results
in
improper
task
completion
backlogs.
To
address
this
issue,
a
Particle
Swarm
Optimization-dependent
Multi-Task
Assignment
Model
(PSO-MTAM)
is
introduced
article.
swarms
initialized
for
available
linear
groups
towards
destination.
This
article
addressed
subject
UAVs
using
multi-task
assignment
paradigm
increase
rates
handling
efficiency.
different
swarm
stages
verified
progression,
resulting
at
final
stage.
In
process,
first
local
best
solution
estimated
rate
single
task.
second
relies
on
reaching
global
identified
depending
convergence
above
solutions
progression
density.
positions
immediately
identified,
synchronous
generate
best.
backlog-generating
revisited
by
reassigning
or
re-initializing
objects.
proposed
model’s
performance
analyzed
rate,
ratio,
processing
time,
Improving
essential
validation,
necessitating
position
updates
from
intermediate
UAVs.
With
varying
densities
degrees
convergence,
iterations
continue
until
completion.
There
an
11%
12.02%
ratio
with
suggested
model.
It
leads
10.84%
decrease
9.91%
backlogs,
12.7%
cost.
Big Data and Cognitive Computing,
Год журнала:
2024,
Номер
8(12), С. 177 - 177
Опубликована: Дек. 2, 2024
Unmanned
aerial
vehicles
(UAVs),
commonly
known
as
drones,
are
being
seen
the
most
promising
type
of
autonomous
in
context
intelligent
transportation
system
(ITS)
technology.
A
key
enabling
factor
for
current
development
ITS
technology
based
on
is
task
allocation
architecture.
This
approach
allows
tasks
to
be
efficiently
assigned
robots
a
multi-agent
system,
taking
into
account
both
robots’
capabilities
and
service
requirements.
Consequently,
this
study
provides
an
overview
application
drones
ITSs,
focusing
applications
algorithms
UAV
networks.
Currently,
there
different
types
that
employed
drone-based
systems,
including
market-based
approaches,
game-theory-based
algorithms,
optimization-based
machine
learning
techniques,
other
hybrid
methodologies.
paper
offers
comprehensive
literature
review
how
such
approaches
utilized
optimize
UAV-based
ITSs.
The
main
characteristics,
constraints,
limitations
detailed
highlight
their
advantages,
achievements,
applicability
Current
research
trends
field
well
gaps
also
thoughtfully
discussed.
IEEE Access,
Год журнала:
2022,
Номер
10, С. 115424 - 115434
Опубликована: Янв. 1, 2022
The
application
of
beam-hopping
technology
to
low
earth
orbit
satellites
can
effectively
achieve
flexible
allocation
and
efficient
utilization
on-board
resources.
Considering
that
the
power
resources
on
are
limited,
electromagnetic
environment
is
complex
changeable,
terminal
distribution
service
requirements
highly
dynamic.
We
established
model,
priority
model
multibeam
resource
scheduling
under
constraints
beam
bandwidth,
power,
priorities,
etc.
To
solve
catastrophic
problem
a
large
solution
space
in
improve
convergence
algorithm,
we
propose
an
enhanced
artificial
bee
colony
algorithm.
optimization
strategy
improves
process
population
initialization,
updates,
search
for
global
optimal
solution.
simulation
results
show
cochannel
interference
utilization,
algorithm
always
converges
objective
function
at
fastest
speed,
which
proves
has
high
applicability
dynamic
characteristics
LEO
satellites.
In
addition,
obtain
solution,
thus,
it
ensure
fairness
effectiveness
completion.
Drones,
Год журнала:
2023,
Номер
7(9), С. 544 - 544
Опубликована: Авг. 22, 2023
Unmanned
aerial
vehicles
(UAVs)
are
extensively
employed
for
urban
image
captures
and
the
reconstruction
of
large-scale
3D
models
due
to
their
affordability
versatility.
However,
most
commercial
flight
software
lack
support
adaptive
capture
multi-view
images.
Furthermore,
limited
performance
battery
capacity
a
single
UAV
hinder
efficient
capturing
scenes.
To
address
these
challenges,
this
paper
presents
novel
method
multi-UAV
continuous
trajectory
planning
aimed
at
reconstructions
scene.
Our
primary
contribution
lies
in
development
path
framework
rooted
task
search
principles.
Within
framework,
we
initially
ascertain
optimal
locations
images
by
assessing
scene
reconstructability,
thereby
enhancing
overall
quality
reconstructions.
curtail
energy
costs
trajectories
allocating
sequences,
characterized
minimal
corners
lengths,
among
multiple
UAVs.
Ultimately,
integrate
considerations
costs,
safety,
reconstructability
into
unified
optimization
process,
facilitating
paths
Empirical
evaluations
demonstrate
efficacy
our
approach
collaborative
full-scene
UAVs,
achieving
low
while
attaining
high-quality
