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PLANNING ALGORITHMS
Steven M. LaValle
Contents
Preface
Part I Introductory Material
Chapter 1 Introduction
Planning to Plan
Motivational Examples and Applications
Basic Ingredients of Planning
Algorithms, Planners, and Plans
1.5 Organization of the Book
Chapter 2 Discrete Planning
Introduction to Discrete Feasible Planning
Searching for Feasible Plans
Discrete Optimal Planning
Using Logic to Formulate Discrete Planning
Logic-Based Planning Methods
Part II Motion Planning
Overview of Part II: Motion Planning
Chapter 3
3.1 Geometric Modeling
Rigid-Body Transformations
Transforming Kinematic Chains of Bodies
Transforming Kinematic Trees
Nonrigid Transformations
Chapter 4
4.1 Basic Topological Concepts
4.2 Defining the Configuration Space
Configuration Space Obstacles
Closed Kinematic Chains
Chapter 5
Distance and Volume in C-Space
Sampling Theory
Collision Detection
Incremental Sampling and Searching
Rapidly Exploring Dense Trees
Roadmap Methods for Multiple Queries
Chapter 6
Introduction
Polygonal Obstacle Regions
Cell Decompositions
Computational Algebraic Geometry
6.5 Complexity of Motion Planning
Chapter 7
7.1 Time-Varying Problems
Multiple Robots
7.3 Mixing Discrete and Continuous Spaces
7.4 Planning for Closed Kinematic Chains
7.5 Folding Problems in Robotics and Biology
Coverage Planning
Optimal Motion Planning
Chapter 8
Motivation
Discrete State Spaces
8.3 Vector Fields and Integral Curves
Complete Methods for Continuous Spaces
Sampling-Based Methods for Continuous Spaces
Part III
Overview of Part III: Decision-Theoretic Planning
Chapter 9
Preliminary Concepts
A Game Against Nature
9.3 Two-Player Zero-Sum Games
Nonzero-Sum Games
9.5 Decision Theory Under Scrutiny
Chapter 10
Introducing Sequential Games Against Na- ture
Algorithms for Computing Feedback Plans
Infinite-Horizon Problems
Reinforcement Learning
Sequential Game Theory
Continuous State Spaces
Chapter 11
Discrete State Spaces
Derived Information Spaces
Examples for Discrete State Spaces
Continuous State Spaces
Examples for Continuous State Spaces
Computing Probabilistic Information States
Information Spaces in Game Theory
Chapter 12
12.1 General Methods
12.2 Localization
Environment Uncertainty and Mapping
Visibility-Based Pursuit-Evasion
Manipulation Planning with Sensing Un- certainty
Part IV
Overview of Part IV:
Chapter 13 Differential Models
Velocity Constraints on the Configuration Space
Phase Space Representation of Dynamical Systems
Basic Newton-Euler Mechanics
Advanced Mechanics Concepts
Multiple Decision Makers
Chapter 14
Introduction
Reachability and Completeness
Sampling-Based Motion Planning Revisited
Incremental Sampling and Searching Meth- ods
Feedback Planning Under Differential Con- straints
Decoupled Planning Approaches
14.7 Gradient-Based Trajectory Optimization
Chapter 15
15.1 Basic System Properties
Continuous-Time Dynamic Programming
Optimal Paths for Some Wheeled Vehicles
Nonholonomic System Theory
Steering Methods for Nonholonomic Sys- tems
Bibliography
Index
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Part I Introductory Material
Part I Introductory Material
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