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Principles of Robot Motion: Theory, Algorithms, and Implementations
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Robot motion planning has become a major focus of robotics. Research findings
can be applied not only to robotics but to planning routes on circuit boards,
directing digital actors in computer graphics, robot-assisted surgery and medicine,
and in novel areas such as drug design and protein folding. This text reflects
the great advances in the field that have taken place in the last ten years, including
sensor-based planning, probabalistic planning, localization and mapping, and motion
planning for dynamic and nonholonomic systems. Its presentation makes the mathematical
underpinnings of robot motion accessible to students of computer science and engineering,
relating low-level implementation details to high-level algorithmic concepts.
Chapters 2-6 treat geometric motion planning approaches, chapter 7 covers probabilistic
methods for geometric planning, chapters 8-9 cover probabilistic methods mainly
for localization, and chapters 10-12 cover dynamic mechanical systems. New mathematical
concepts are introduced in an intuitive manner on an as-needed basis; the appendix
contains further background on topics including graph theory, probability, filtering,
and statistics. The broad range of robot motion applications is reflected in the
broad spectrum of expertise represented by the seven coauthors, each of whom worked
on all of the twelve chapters to create a fully integrated text.
About the Authors
Howie Choset is Associate Professor in Mechanical Engineering
and in the Robotics Institute, Carnegie Mellon University
Kevin M. Lynch is Associate Professor in the Mechanical Engineering
Department, Northwestern University.
Seth Hutchinson is Professor in the Department of Electrical
and Computer Engineering, University of Illinois at Urbana-Champaign.
George Kantor is Project Scientist in the Center for the Foundations
of Robotics, Robotics Institute, Carnegie Mellon University.
Wolfram Burgard is Professor of Computer Science, University
of Freiburg.
Lydia E. Kavraki is Associate Professor of Computer Science
and Bioengineering, Rice University.
Sebastian Thrun is Associate Professor of Computer Science,
Stanford University, the Director of Stanford's AI Lab, and General Chair of
the 2003 NIPS conference.
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