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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
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Mobile Robot Localization and Map Building - A Multisensor Fusion Approach (Hardcover, 1999 ed.)
Loot Price: R4,353
Discovery Miles 43 530
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Mobile Robot Localization and Map Building - A Multisensor Fusion Approach (Hardcover, 1999 ed.)
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During the last decade, many researchers have dedicated their
efforts to constructing revolutionary machines and to providing
them with forms of artificial intelligence to perform some of the
most hazardous, risky or monotonous tasks historically assigned to
human beings. Among those machines, mobile robots are undoubtedly
at the cutting edge of current research directions. A rough
classification of mobile robots can be considered: on the one hand,
mobile robots oriented to human-made indoor environments; on the
other hand, mobile robots oriented to unstructured outdoor
environments, which could include flying oriented robots,
space-oriented robots and underwater robots. The most common motion
mechanism for surface mobile robots is the wheel-based mechanism,
adapted both to flat surfaces, found in human-made environments,
and to rough terrain, found in outdoor environments. However, some
researchers have reported successful developments with leg-based
mobile robots capable of climbing up stairs, although they require
further investigation. The research work presented here focuses on
wheel-based mobile robots that navigate in human-made indoor
environments. The main problems described throughout this book are:
Representation and integration of uncertain geometric information
by means of the Symmetries and Perturbations Model (SPmodel). This
model combines the use of probability theory to represent the
imprecision in the location of a geometric element, and the theory
of symmetries to represent the partiality due to characteristics of
each type of geometric element. A solution to the first location
problem, that is, the computation of an estimation for the mobile
robot location when the vehicle is completely lost in the
environment. The problem is formulated as a search in an
interpretation tree using efficient matching algorithms and
geometric constraints to reduce the size of the solution space. The
book proposes a new probabilistic framework adapted to the problem
of simultaneous localization and map building for mobile robots:
the Symmetries and Perturbations Map (SPmap). This framework has
been experimentally validated by a complete experiment which
profited from ground-truth to accurately validate the precision and
the appropriateness of the approach. The book emphasizes the
generality of the solutions proposed to the different problems and
their independence with respect to the exteroceptive sensors
mounted on the mobile robot. Theoretical results are complemented
by real experiments, where the use of multisensor-based approaches
is highlighted.
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