1.5 Organization of the Book

Here is a brief overview of the book. See also the overviews at the beginning of Parts II-IV.

PART I: Introductory Material
This provides very basic background for the rest of the book.

PART II: Motion Planning
The main source of inspiration for the problems and algorithms covered in this part is robotics. The methods, however, are general enough for use in other applications in other areas, such as computational biology, computer-aided design, and computer graphics. An alternative title that more accurately reflects the kind of planning that occurs is ``Planning in Continuous State Spaces.''

PART III: Decision-Theoretic Planning
An alternative title to Part III is ``Planning Under Uncertainty.'' Most of Part III addresses discrete state spaces, which can be studied immediately following Part I. However, some sections cover extensions to continuous spaces; to understand these parts, it will be helpful to have read some of Part II.

PART IV: Planning Under Differential Constraints
This can be considered as a continuation of Part II. Here there can be both global (obstacles) and local (differential) constraints on the continuous state spaces that arise in motion planning. Dynamical systems are also considered, which yields state spaces that include both position and velocity information (this coincides with the notion of a state space in control theory or a phase space in physics and differential equations).

Steven M LaValle 2012-04-20