Applied Sciences,
Год журнала:
2024,
Номер
14(20), С. 9469 - 9469
Опубликована: Окт. 17, 2024
This
paper
addresses
the
development
of
a
vision
system
for
UR5
cobot
and
corresponding
operating
algorithm
robotic
quality
control
station.
The
hardware–software
architecture
developed
station
consisting
equipped
with
web
camera
stationary
industrial
lighting
is
presented.
Image
processing
analysis
algorithms
are
described,
method
communication
between
components
discussed,
scenarios
presented
as
single
part
line.
Based
on
results
which
were
obtained,
level
measurement
noise,
accuracy,
repeatability
estimated.
A
novel
complete
modules
shown
discussed.
software
based
Python
3.12
language,
OpenCV
4.7.0.68
libraries,
PolyScope
1.8
environment
incorporates
calibration,
image
acquisition,
preprocessing
(for
objects’
location
geometric
measurements)
cell
control.
hardware
PC
two
independent
distinct
cameras:
one
permanently
affixed
other
mounted
to
cobot’s
flange.
innovative
setup,
combined
architecture,
broadens
scope
existing
applications.
Sensors,
Год журнала:
2025,
Номер
25(3), С. 765 - 765
Опубликована: Янв. 27, 2025
This
article
focuses
on
the
integration
of
Internet
Things
(IoT)
and
Robotic
Things,
representing
a
dynamic
research
area
with
significant
potential
for
industrial
applications.
The
(IoRT)
integrates
IoT
technologies
into
robotic
systems,
enhancing
their
efficiency
autonomy.
provides
an
overview
used
in
IoRT,
including
hardware
components,
communication
technologies,
cloud
services.
It
also
explores
IoRT
applications
industries
such
as
healthcare,
agriculture,
more.
discusses
challenges
future
directions,
data
security,
energy
efficiency,
ethical
issues.
goal
is
to
raise
awareness
importance
demonstrate
how
this
technology
can
bring
benefits
across
various
sectors.
PLoS ONE,
Год журнала:
2025,
Номер
20(1), С. e0314347 - e0314347
Опубликована: Янв. 16, 2025
Industry
4.0
has
transformed
manufacturing
with
the
integration
of
cutting-edge
technology,
posing
crucial
issues
in
efficient
task
assignment
to
multi-tasking
robots
within
smart
factories.
The
paper
outlines
a
unique
method
decentralizing
auctions
handle
basic
tasks.
It
also
introduces
an
improved
variant
Binary
Particle
Swarm
Optimization
(IBPSO)
algorithm
manage
complicated
tasks
that
require
multi-robot
collaboration.
main
contributions
we
make
are:
design
auction
decentralization
(AOCTA)
which
allows
for
and
flexible
distribution
dynamic
contexts,
optimization
coalition
formation
complex
jobs
by
using
IBPSO
improves
efficiency
energy
decreases
cost
computation
as
well
thorough
simulations
show
our
proposed
significantly
surpasses
conventional
methods
efficiency,
completion
rates
terms
usage,
rate,
scaling
system.
This
research
contributes
development
through
providing
effective
solution
aligns
sustainability
objectives
addresses
operational
environmental
impacts.
Addressing
challenges
posed
allocation
distributed
systems,
these
advanced
technologies
provide
comprehensive
solution,
facilitating
evolution
innovative
systems.
Information,
Год журнала:
2025,
Номер
16(2), С. 79 - 79
Опубликована: Янв. 22, 2025
The
application
of
modern
machine
learning
methods
in
industrial
settings
is
a
relatively
new
challenge
and
remains
the
early
stages
development.
Current
computational
power
enables
processing
vast
numbers
production
parameters
real
time.
This
article
presents
practical
analysis
welding
process
robotic
cell
using
unsupervised
HDBSCAN
algorithm,
highlighting
its
advantages
over
classical
k-means
algorithm.
paper
also
addresses
problem
predicting
monitoring
undesirable
situations
proposes
use
real-time
graphical
representation
noisy
data
as
particularly
effective
solution
for
managing
such
issues.
Environmental Earth Sciences,
Год журнала:
2025,
Номер
84(4)
Опубликована: Фев. 1, 2025
Abstract
The
Hindukush-Himalayan
(HKH)
region,
known
for
its
eco-environmental
importance,
has
been
witnessing
transformations
in
recent
years
governed
by
factors
such
as
climate
variability,
land
use
shifts,
and
population
growth.
These
changes
have
profound
implications
regional
sustainability,
water
resources,
livelihood.
This
study
attempts
to
explore
the
spatial
temporal
variability
selected
environmental
parameters
including
surface
temperature
(LST),
normalized
difference
vegetation
index
(NDVI),
precipitation
patterns,
snow
(NDSI),
cover
(LULC)
from
1990
2022
using
Landsat
imageries
(30
m
resolution),
CHIRPS
data
at
0.05°
resolution.
area
spans
32,000
km
2
covering
two
major
political/administrative
divisions
(Malakand
Hazara)
HKH
region
of
Pakistan.
was
primarily
because
unprecedented
over
last
three
decades.
For
detailed
analysis,
divided
into
five
elevation
zones
LST,
NDVI,
NDSI,
LULC
analyses
were
conducted
utilizing
Google
Earth
Engine
(GEE)
platform
engine.
results
revealed
a
notable
rise
LST
lowest
zone.
NDVI
noticeable
decline
5988
1990,
4225
2010,
followed
growth
7669
2022,
since
2010
after
launching
Billion
Tree
Tsunami
Afforestation
Project
(BTTAP)
2013.
Likewise,
patterns
exhibit
transitioning
low
high
levels.
However,
most
finding
is
marked
covered
7000
3800
between
2022.
