Control Systems and Optimization Letters,
Journal Year:
2024,
Volume and Issue:
2(3), P. 274 - 284
Published: Nov. 25, 2024
Human-robot
cooperation
(HRC)
is
becoming
increasingly
essential
in
many
different
sectors
such
as
industry,
healthcare,
agriculture,
and
education.
This
between
robot
human
has
advantages
increasing
boosting
productivity
efficiency,
executing
the
task
easily,
effectively,
a
fast
time,
minimizing
efforts
time.
Therefore,
ensuring
safety
issues
during
this
are
critical
must
be
considered
to
avoid
or
minimize
any
risk
danger
whether
for
robot,
human,
environment.
Risks
may
accidents
system
failures.
In
paper,
an
overview
of
human-robot
discussed.
The
main
key
challenges
robotics
outlined
presented
collision
detection
avoidance,
adapting
unpredictable
behaviors,
implementing
effective
mitigation
strategies.
difference
industrial
robots
cobots
illustrated.
Their
features
also
provided.
problem
avoidance
environment
defined
discussed
detail.
result
paper
can
guideline
framework
future
researchers
design
development
their
methods
tasks.
addition,
it
shapes
research
directions
measures.
World Electric Vehicle Journal,
Journal Year:
2025,
Volume and Issue:
16(3), P. 144 - 144
Published: March 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.
Robotica,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 24
Published: March 10, 2025
Abstract
Global
path
planning
using
roadmap
(RM)
path-planning
methods
including
Voronoi
diagram
(VD),
rapidly
exploring
random
trees
(RRT),
and
probabilistic
(PRM)
has
gained
popularity
over
the
years
in
robotics.
These
global
are
usually
combined
with
other
techniques
to
achieve
collision-free
robot
control
a
specified
destination.
However,
it
is
unclear
which
of
these
best
choice
compute
efficient
terms
length,
computation
time,
safety,
consistency
computation.
This
article
reviewed
adopted
comparative
research
methodology
perform
analysis
determine
efficiency
optimality,
consistency,
time.
A
hundred
maps
different
complexities
obstacle
occupancy
rates
ranging
from
50.95%
78.42%
were
used
evaluate
performance
RM
methods.
Each
method
demonstrated
unique
strengths
limitations.
The
study
provides
critical
insights
into
their
relative
performance,
highlighting
application-specific
recommendations
for
selecting
most
suitable
method.
findings
contribute
advancing
by
offering
detailed
evaluation
widely
SAE technical papers on CD-ROM/SAE technical paper series,
Journal Year:
2025,
Volume and Issue:
1
Published: April 1, 2025
<div
class="section
abstract"><div
class="htmlview
paragraph">Autonomous
ground
navigation
has
advanced
significantly
in
urban
and
structured
environments,
supported
by
the
availability
of
comprehensive
datasets.
However,
navigating
complex
off-road
terrains
remains
challenging
due
to
limited
datasets,
diverse
terrain
types,
adverse
environmental
conditions,
sensor
limitations
affecting
vehicle
perception.
This
study
presents
a
review
integrating
their
applications
with
technologies
traversability
analysis
methods.
It
identifies
critical
gaps,
including
class
imbalances,
performance
under
existing
estimation
approaches.
Key
contributions
include
novel
classification
datasets
based
on
annotation
methods,
providing
insights
into
scalability
applicability
across
terrains.
The
also
evaluates
conditions
proposes
strategies
for
incorporating
event-based
hyperspectral
cameras
enhance
perception
systems.
Additionally,
we
address
lack
unified
evaluation
metrics
introducing
qualifiers
assessing
perception,
planning,
control
Finally,
comparison
geometry-based,
learning-based,
probabilistic
methods
navigability
prediction
highlights
importance
multi-sensor
data
integration
improved
decision-making.
These
actionable
recommendations
aim
guide
development
adaptive
robust
autonomous
systems,
advancing
real-world
environments.</div></div>
Sustainability,
Journal Year:
2025,
Volume and Issue:
17(8), P. 3383 - 3383
Published: April 10, 2025
Efficient
traffic
management
in
urban
areas
represents
a
key
challenge
for
modern
cities,
particularly
the
context
of
sustainable
development
and
reducing
negative
environmental
impacts.
This
paper
explores
application
artificial
intelligence
(AI)
optimizing
through
combination
reinforcement
learning
(RL)
predictive
analytics.
The
focus
is
on
simulating
network
Belgrade
(Serbia,
Europe),
where
RL
algorithms,
such
as
Deep
Q-Learning
Proximal
Policy
Optimization,
are
used
dynamic
signal
control.
model
optimized
operations
at
intersections
with
high
volumes
using
real-time
data
from
IoT
sensors,
computer
vision-enabled
cameras,
third-party
mobile
usage
connected
vehicles.
In
addition,
implemented
analytics
leverage
time
series
models
(LSTM,
ARIMA)
graph
neural
networks
(GNNs)
to
anticipate
congestion
bottlenecks,
enabling
initiative-taking
decision-making.
Special
attention
given
challenges
transmission
delays,
system
scalability,
ethical
implications,
proposed
solutions
including
edge
computing
distributed
models.
Results
simulation
demonstrate
significant
advantages
AI
370
control
devices
installed
fixed
timing
systems
adaptive
systems,
an
average
reduction
waiting
times
by
33%,
resulting
16%
decrease
greenhouse
gas
emissions
improved
safety
(measured
number
accidents).
A
limitation
this
that
it
does
not
offer
system’s
adaptability
temporary
surges
during
mass
events
or
severe
weather
conditions.
finding
integrating
into
consists
fixed-timing
lights
approach
improving
quality
life
large
cities
like
achieving
smart
city
objectives.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: April 12, 2025
Path
planning
is
the
process
by
which
an
autonomous
robot
obtains
information
about
its
environment
and
chooses
best
route
from
start
point
to
target
destination
while
avoiding
obstacles.
It
vital
success
of
operation
as
it
provides
maneuverability
within
environment,
ensuring
a
collision-free
optimum
path
that
guarantees
efficient
movement.
This
paper
introduces
categorizes
several
notable
path-planning
algorithms
used
in
robotics
operations.
We
delve
into
their
basic
principles,
key
features,
challenges,
real-world
applications.
Additionally,
we
provided
simulated
comparison
result
algorithms.
Finally,
analyze
outcomes,
give
concise
conclusion,
forecast
future
trends
techniques.
Results in Engineering,
Journal Year:
2024,
Volume and Issue:
23, P. 102625 - 102625
Published: July 27, 2024
The
Vector
Field
Histogram
Plus
(VFH+)
algorithm
is
a
cornerstone
in
robotic
navigation,
renowned
for
its
efficiency
and
straightforward
implementation
across
multitude
of
environments.
Despite
widespread
utility,
the
algorithm's
inherent
limitations
handling
complex
obstacle
entrapments
necessitate
refinement.
This
paper
presents
an
advanced
iteration,
designated
as
VFH
+
T,
which
incorporates
sophisticated
memory-based
trap
recognition
avoidance
mechanisms.
enhancement
facilitates
dynamic
adjustment
navigation
strategies
through
integration
geometrical
rules
that
retrospectively
inform
path
planning
decisions.
Moreover,
T
intricately
melds
platform's
kinematic
constraints,
optimizing
real-time
navigational
commands
based
on
both
current
sensory
input
historical
environmental
interactions.
Empirical
simulations
validate
enhanced
proficiency
circumventing
traps,
improving
operational
safety
efficiency.
Comparative
analysis
with
VFH+
VFH*
algorithms
show
up
to
17
%
reduction
traveling
distance
due
trap-avoidance
technique
during
navigation.
advancement
holds
significant
implications
enhancing
autonomous
technologies
various
practical
applications,
from
self-driving
vehicles
aids
logistics
service
industries.
