Simulation-Based Performance Assessment of ORB, YOLOv8, and Picking Strategies for Single-Arm Robot Conveyor Belt Pick-and-Place Operations
Research Square (Research Square),
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 7, 2025
Abstract
Pick-and-place
robots
play
a
crucial
role
in
industrial
automation,
helping
to
lower
labor
costs,
minimize
errors,
and
improve
production
efficiency.
Many
image
processing
methods
have
been
proposed
facilitate
the
pick-and-place
operation.
However,
performance
of
these
is
sensitive
lighting
conditions,
presence
occlusions,
variations
object
appearance.
Although
many
challenges
can
be
overcome
through
use
deep
learning
methods,
direct
comparison
coupled
with
an
analysis
different
picking
strategies,
lacking.
The
present
study
addresses
this
gap
by
conducting
simulation-based
evaluation
accuracy
time
ORB
algorithm
YOLOv8
model
for
recognition.
effects
two
strategies
(FIFO
Euclidean
Distance)
on
system
throughput
are
also
explored.
simulation
results
show
that
achieves
higher
(98%)
significantly
faster
(138
ms)
than
(97.33%
715.24
ms
time).
Additionally,
FIFO
strategy
improves
productivity
13%
compared
Distance
strategy.
Overall,
findings
provide
valuable
insights
into
optimizing
robotic
operations
automation
settings.
Язык: Английский
Live digital twin with virtual reality for accessible and immersive manufacturing education
The International Journal of Advanced Manufacturing Technology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 23, 2025
Язык: Английский