Principles of Robot Motion

Theory, Algorithms, and Implementations

by Howie Choset, Kevin M. Lynch, Seth Hutchinson, George A. Kantor, Wolfram Burgard, Lydia E. Kavraki and Sebastian Thrun

ISBN: 9780262332514 | Copyright 2005

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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 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, rleating low-level implementation details to high-level algorithmic concepts.

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Foreword (pg. xv)
Preface (pg. xvii)
Acknowledgments (pg. xxi)
1 Introduction (pg. 1)
2 Bug Algorithms (pg. 17)
3 Configuration Space (pg. 39)
4 Potential Functions (pg. 77)
5 Roadmaps (pg. 107)
6 Cell Decompositions (pg. 161)
7 Sampling-Based Algorithms (pg. 197)
8 Kalman Filtering (pg. 269)
9 Bayesian Methods (pg. 301)
10 Robot Dynamics (pg. 349)
11 Trajectory Planning (pg. 373)
12 Nonholonomic and Underactuated Systems (pg. 401)
A Mathematical Notation (pg. 473)
B Basic Set Definitions (pg. 475)
C Topology and Metric Spaces (pg. 478)
D Curve Tracing (pg. 487)
E Representations of Orientation (pg. 489)
F Polyhedral Robots in Polyhedral Worlds (pg. 499)
G Analysis of Algorithms and Complexity Classes (pg. 513)
H Graph Representation and Basic Search (pg. 521)
I Statistics Primer (pg. 547)
J Linear Systems and Control (pg. 552)
Bibliography (pg. 565)
Index (pg. 597)
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