Page 26 - Introduction to Autonomous Mobile Robots

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Introduction
lar talents of each form of locomotion. But designing a robot’s locomotive system properly
requires the ability to evaluate its overall motion capabilities quantitatively. Chapter 3,
“Mobile Robot Kinematics”, applies principles of kinematics to the whole robot, beginning
with the kinematic contribution of each wheel and graduating to an analysis of robot
maneuverability enabled by each mobility mechanism configuration.
The greatest single shortcoming in conventional mobile robotics is, without doubt, per-
ception: mobile robots can travel across much of earth’s man-made surfaces, but they
cannot perceive the world nearly as well as humans and other animals. Chapter 4, “Percep-
tion”, begins a discussion of this challenge by presenting a clear language for describing
the performance envelope of mobile robot sensors. With this language in hand, chapter 4
goes on to present many of the off-the-shelf sensors available to the mobile roboticist,
describing their basic principles of operation as well as their performance limitations. The
most promising sensor for the future of mobile robotics is vision, and chapter 4 includes an
overview of the theory of operation and the limitations of both charged coupled device
(CCD) and complementary metal oxide semiconductor (CMOS) sensors.
But perception is more than sensing. Perception is also the interpretation of sensed data
in meaningful ways. The second half of chapter 4 describes strategies for feature extraction
that have been most useful in mobile robotics applications, including extraction of geomet-
ric shapes from range-based sensing data, as well as landmark and whole-image analysis
using vision-based sensing.
Armed with locomotion mechanisms and outfitted with hardware and software for per-
ception, the mobile robot can move and perceive the world. The first point at which mobil-
ity and sensing must meet is localization: mobile robots often need to maintain a sense of
position. Chapter 5, “Mobile Robot Localization”, describes approaches that obviate the
need for direct localization, then delves into fundamental ingredients of successful local-
ization strategies: belief representation and map representation. Case studies demonstrate
various localization schemes, including both Markov localization and Kalman filter local-
ization. The final part of chapter 5 is devoted to a discussion of the challenges and most
promising techniques for mobile robots to autonomously map their surroundings.
Mobile robotics is so young a discipline that it lacks a standardized architecture. There
is as yet no established robot operating system. But the question of architecture is of para-
mount importance when one chooses to address the higher-level competences of a mobile
robot: how does a mobile robot navigate robustly from place to place, interpreting data,
localizing and controlling its motion all the while? For this highest level of robot compe-
tence, which we term navigation competence, there are numerous mobile robots that show-
case particular architectural strategies. Chapter 6, “Planning and Navigation”, surveys the
state of the art of robot navigation, showing that today’s various techniques are quite sim-
ilar, differing primarily in the manner in which they decompose the problem of robot con-