Candidate:
Olzhas
Adiyatov
Title:
Path
Planning
Framework
for
Unmanned
Ground
Vehicles
on
Uneven
Terrains
Date:
August
9,
2022
Time:
14:00
Place:
online
Supervisor(s):
Smith,
Stephen
L.
-
Fidan,
Baris
Abstract:
In
this
thesis,
I
address
the
problem
of
long-range
path
planning
on
uneven
terrain
for
non-holonomic
wheeled
mobile
robots
(WMR).
Uneven
terrain
path
planning
is
essential
for
search-and-rescue,
m
surveillance,
military,
humanitarian,
agricultural,
constructing
missions,
etc.
These
missions
necessitate
generation
of
a
feasible
sequence
of
waypoints,
or
reference
states,
to
navigate
a
wheeled
mobile
robot
(WMR)
from
the
initial
location
to
the
final
target
location
through
the
uneven
terrain.
Feasibility
of
navigating
through
a
given
path
over
an
uneven
terrain
can
be
undermined
by
various
terrain
features.
Examples
of
such
features
are
loose
soil,
vegetation,
boulders,
steeply
sloped
terrain,
or
a
combination
of
all
these
elements.
I
propose
a
three-stage
framework
that
solves
the
problem
of
rapid
path
planning
on
a
long
range.
These
stages
improve
the
solution
quality
at
each
stage
of
the
path
planning
framework.
RRT-Connect
is
used
for
rapid
discovery
of
the
feasible
solution.
Followed
by
the
Informed
RRT*
that
improves
the
feasible
solution.
Finally,
shortcut
heuristics
locally
improves
solution.
The
PCA-based
accelerated
version
of
the
traversability
estimation
on
point
cloud
was
proposed
to
improve
the
computational
speed
of
the
path
planning
algorithms
employed
in
the
path
planning
framework.
The
benchmarks
demonstrated
the
efficacy
of
the
approach.
Tuesday, August 9, 2022 2:00 pm
-
2:00 pm
EDT (GMT -04:00)