Introduction to Path Planning and
Obstacle Avoidance
A basic requirement of a mobile autonomous vehicle is
path planning. With the vehicle in an
arbitrary initial position A we wish to issue a desired goal
position B (including orientation)
and have the v

Voronoi Methods
Voronoi diagrams are elegant geometric
constructions 4 that find applications
throughout
computer science | one is shown in figure 2.4.
Points on a 2D-Voronoi diagram are equidistant from the nearest two objects in the
real world. So the V

The Minkowski-Sum
Real robots have arbitrary shapes and these shapes make
for complicated interactions with
obstacles which we would like to simplify. One way to do
this is to transform the problem
to one in which the robot can be considered as a pointobj

Holonomicity
Holonomicity is the term used to describe the locomotive
properties of a vehicle with respect
to its workspace. We will introduce a mathematical
definition of the term shortly but we
will begin by stating, in words, a denition:
A vehicle is h

Bug Methods
The generation of a global Voronoi diagram requires
upfront knowledge of the environment.
In many cases this is unrealistic. Also Voronoi planners by
definition keep the vehicle as far
away from objects as possible - this can have two side
eec

Estimation - A Quick Revision
Introduction
This lecture will begin to cover a topic central to mobile
robotics | Estimation. There
is a vast literature on Estimation Theory encompassing a rich
variation of techniques and
ideas. We shall focus on some of t

Simultaneous Localisation
and Mapping SLAM
SLAM is the generalised navigation problem. It asks if it is
possible for a robot, starting
with no prior information, to move through its
environment and build a consistent map of
the entire environment. Additio

Feature Based
Localisation
This is the simplest task. We are given a map M
containing a set of features and a stream
of observations of measurements between the
vehicle and these features (see figure 7.3). We
assume to begin with that an oracle is telling

Dead-Reckoned Odometry
Measurements
The model is used velocity and steer angles as control
input into the model. It is
common to find that this low level knowledge is not
easy to obtain or that the relationship
between control, prior and prediction is not

Simulation Model
The simulation model is non-linear. This of course is
realistic | we may model the world
within our filter as a well behaved linear system 7 but the
physics of the real world can be
relied upon to conspire to yield something far more
comp