Path Planning for Dragon-Fruit-Harvesting Robotic Arm Based on XN-RRT* Algorithm
Sensors,
Год журнала:
2025,
Номер
25(9), С. 2773 - 2773
Опубликована: Апрель 27, 2025
This
paper
proposes
an
enhanced
RRT*
algorithm
(XN-RRT*)
to
address
the
challenges
of
low
path
planning
efficiency
and
suboptimal
picking
success
rates
in
complex
pitaya
harvesting
environments.
The
generates
sampling
points
based
on
normal
distribution
dynamically
adjusts
center
range
according
target
distance
tree
density,
thus
reducing
redundant
sampling.
An
improved
artificial
potential
field
method
is
employed
during
expansion,
incorporating
adjustment
factors
refine
guidance
overcome
local
optima
infeasible
targets.
A
greedy
then
used
remove
nodes,
shorten
path,
apply
cubic
B-spline
curves
smooth
improving
stability
continuity
robotic
arm.
Simulations
both
two-dimensional
three-dimensional
environments
demonstrate
that
XN-RRT*
performs
effectively,
with
fewer
iterations,
high
convergence
efficiency,
superior
quality.
simulation
a
six-degree-of-freedom
arm
orchard
environment
using
ROS2
platform
shows
achieves
98%
rate,
outperforming
by
90.32%,
27.12%
reduction
length
14%
increase
rate.
experimental
results
confirm
proposed
exhibits
excellent
overall
performance
environments,
offering
valuable
reference
for
planning.
Язык: Английский
Research on the A* Algorithm Based on Adaptive Weights and Heuristic Reward Values
World Electric Vehicle Journal,
Год журнала:
2025,
Номер
16(3), С. 144 - 144
Опубликована: Март 4, 2025
Aiming
at
the
problems
of
A*
algorithm’s
long
running
time,
large
number
search
nodes,
tortuous
paths,
and
planned
paths
being
prone
to
colliding
with
corner
points
obstacles,
adaptive
weighting
reward
value
theory
are
proposed
improve
it.
Firstly,
diagonal-free
five-way
based
on
coordinate
changes
is
used
make
algorithm
purposeful.
Meanwhile,
in
order
path
security,
diagonal
filtered
out
when
there
obstacles
neighborhood.
Secondly,
a
radial
basis
function
act
as
coefficient
heuristic
adjust
proportion
functions
accordingly
distance.
Again,
optimize
cost
using
provided
by
target
point
so
that
current
away
from
local
optimum.
Finally,
secondary
optimization
performed
increase
distance
between
barriers,
optimized
smoothed
Bessel
curves.
Typical
working
conditions
selected,
verified
through
simulation
tests.
Simulation
tests
show
not
only
shortens
planning
time
improves
security
but
also
reduces
nodes
about
76.4%
average
turn
angle
71.7%
average.
Язык: Английский
Hybrid Optimization of Horizontal Alignments in European Terrains: A Comparative Study
Lecture notes in computer science,
Год журнала:
2025,
Номер
unknown, С. 119 - 136
Опубликована: Янв. 1, 2025
Язык: Английский
Mobile robot for leaf disease detection and precise spraying: Convolutional neural networks integration and path planning
Youssef Bouhaja,
Hatim Bamoumen,
Israe Derdak
и другие.
Scientific African,
Год журнала:
2025,
Номер
unknown, С. e02717 - e02717
Опубликована: Апрель 1, 2025
Язык: Английский
Multi-Autonomous Underwater Vehicle Full-Coverage Path-Planning Algorithm Based on Intuitive Fuzzy Decision-Making
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(8), С. 1276 - 1276
Опубликована: Июль 29, 2024
Aiming
at
the
difficulty
of
realizing
full-coverage
path
planning
in
a
multi-AUV
collaborative
search,
path-planning
algorithm
based
on
intuitionistic
fuzzy
decision-making
is
proposed.
First,
state
space
model
search
environment
was
constructed
using
raster
method
to
provide
accurate
change
data
for
AUV.
Second,
intuition-based
decision-making,
and
more
uncertain
underwater
information
modeled
decision
algorithm.
A
priority
strategy
used
avoid
obstacles
area.
Finally,
simulation
experiment
verified
proposed
The
results
demonstrate
that
can
effectively
realize
area,
reduce
generation
repeated
paths.
Язык: Английский
A-Star (A*) with Map Processing for the Global Path Planning of Autonomous Underwater and Surface Vehicles Operating in Large Areas
Applied Sciences,
Год журнала:
2024,
Номер
14(17), С. 8015 - 8015
Опубликована: Сен. 7, 2024
The
global
path
planning
system
is
one
of
the
basic
systems
ensuring
autonomous
operation
unmanned
underwater
vehicles
(UUVs)
and
surface
(USVs)
in
a
complex
aquatic
environment.
A*
algorithm
most
well-known
algorithms
used
to
obtain
an
almost
optimal
path,
avoiding
obstacles
even
environment
containing
objects
with
specific
shapes
non-uniform
arrangements.
main
disadvantage
this
computational
cost
calculation.
This
article
presents
new
approach
based
on
image
processing
map
before
determining
using
A*.
results
numerical
research
large-sized
expressing
port
area
confirm
proposed
method’s
effectiveness,
which
reduces
calculation
time
by
over
500
times
slight
increase
length
compared
version
algorithm.
Based
obtained
results,
also
increases
path’s
safety
designating
narrow
risky
areas
as
closed
vehicle
movement.
For
reason,
method
seems
suitable
for
use
(AUVs)
(ASVs)
operating
large
areas.
Язык: Английский