Principles of Robot Motion
Theory, Algorithms, and Implementation

Howie M. Choset
Kevin Lynch
Sebastian Thrun
Lydia E. Kavraki
Wolfram Burgard

ISBN: 0262033275

 

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.