Principles of Robot Motion: Theory, Algorithms, and Implementations

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Overview

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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Product Details

Meet the Author

Howie Choset is Associate Professor in the Robotics Institute at Carnegie MellonUniversity.

Kevin M. Lynch is Associate Professor in the Mechanical Engineering Department, NorthwesternUniversity.

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, RoboticsInstitute, Carnegie Mellon University.

Wolfram Burgard is Professor of Computer Science and Head of the research lab for AutonomousIntelligent Systems at the University of Freiburg.

Lydia E. Kavraki is Professor of Computer Science and Bioengineering, Rice University.

Sebastian Thrun is Associate Professor in the Computer Science Department at StanfordUniversity and Director of the Stanford AI Lab.

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Table of Contents

1 Introduction 1
2 Bug algorithms 17
3 Configuration space 39
4 Potential functions 77
5 Roadmaps 107
6 Cell decompositions 161
7 Sampling-based algorithms 197
8 Kalman filtering 269
9 Bayesian methods 301
10 Robot dynamics 349
11 Trajectory planning 373
12 Nonholonomic and underactuated systems 401
A Mathematical notation 473
B Basic set definitions 475
C Topology and metric spaces 478
D Curve tracing 487
E Representations of orientation 489
F Polyhedral robots in polyhedral worlds 499
G Analysis of algorithms and complexity classes 513
H Graph representation and basic search 521
I Statistics primer 547
J Linear systems and control 552
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