Preface
Peter C0rke
The practice of robotics and computer vision
each involve the application of computational algo-
rithms to data. The research community has devel-
oped a very large body of algorithms but for a
newcomer to the field this can be quite daunting.
For more t han 10 years t he author has m aintained two op en-
source
matlab
®
Toolboxes, one for robotics and one for vision.
They provide implementations of many important algorithms and
allow users to work with real problems, not just trivial examples.
This new book makes the fundamental algorithms of robotics,
vision and control accessible to all. It weaves together theory, algo-
rithms and examples in a narrative that covers robotics and com-
puter vision separately and together. Using the latest versions
of the Toolboxes the author shows how complex prob lems can be
decomposed and solved using just a few simple lines of code.
The topics covered are guided by real problems observed by the
author over many years as a practitioner of both robotics and
computer vision. It is w ritten in a light but informative style, it is
easy to read and absorb, and includes over 1000
matlab
®
and
Simulink
®
examples and figures. The book is a real walk through
the fundamentals of mobile robots, navigation, localization, arm-
robot kinematics, dynamics and joint level control, then camera
models, image processing, feature extraction and multi-view
geometry, and finally bringing it all together with an extensive
discussion of visual servo systems.
Peter Corke
Robotics,
Vision
and
Control
Robotics, Vision and Control
isbn 978-3-642-20143-1
1
›
springer.com
123
Corke
FUNDAMENTAL
ALGORITHMS
IN MATLAB®
783642 2014319
Robotics,
Vision
and
Control
This, the third release of the Toolbox, represents a
decade of development. The last release was in 2005
and this version captures a large number of changes
over that period but with extensive work over the
last two years to support my new book “Robotics,
Vision & Control” shown to the left.
The Machine Vision Toolbox (MVTB) provides
many functions that are useful in machine vision
and vision-based control. It is a somewhat eclec-
tic collection reflecting my personal interest in areas
of photometry, photogrammetry, colorimetry. It in-
cludes over 100 functions spanning operations such
as image file reading and writing, acquisition, dis-
play, filtering, blob, point and line feature extrac-
tion, mathematical morphology, homographies, vi-
sual Jacobians, camera calibration and color space conversion. The Toolbox, combined
with MATLAB
R
and a modern workstation computer, is a useful and convenient en-
vironment for investigation of machine vision algorithms. For modest image sizes the
processing rate can be sufficiently “real-time” to allow for closed-loop control. Fo-
cus of attention methods such as dynamic windowing (not provided) can be used to
increase the processing rate. With input from a firewire or web camera (support pro-
vided) and output to a robot (not provided) it would be possible to implement a visual
servo system entirely in MATLAB
R
.
An image is usually treated as a rectangular array of scalar values representing inten-
sity or perhaps range. The matrix is the natural datatype for MATLAB
R
and thus
makes the manipulation of images easily expressible in terms of arithmetic statements
in MATLAB
R
language. Many image operations such as thresholding, filtering and
statistics can be achieved with existing MATLAB
R
functions. The Toolbox extends
this core functionality with M-files that implement functions and classes, and mex-files
for some compute intensive operations. It is possible to use mex-files to interface with
image acquisition hardware ranging from simple framegrabbers to robots. Examples
for firewire cameras under Linux are provided.
The routines are written in a straightforward manner which allows for easy under-
standing. MATLAB
R
vectorization has been used as much as possible to improve
efficiency, however some algorithms are not amenable to vectorization. If you have the
Machine Vision Toolbox for MATLAB
R
4 Copyright
c
Peter Corke 2015
