Principles of Robot Motion: Theory, Algorithms, and Implementations (Hardcover)

Description:

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.

Howie Choset is Associate Professor in the Robotics Institute at 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 Associate Professor and Head of the Autonomous Intelligent Systems Research Lab in the Department of Computer Science 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 Stanford University and Director of the Stanford AI Lab.

 

Table of Contents:

Forward	xv
	Preface	xvii
	Acknowledgments	xxi
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 Representations and Basic Search	521
I	Statistics Primer	547
J	Linear Systems and Control	552
	Bibiolography	565
	Index	597