Planning Algorithms

Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. This free book can be downloaded in pdf and html formats.

Book Description

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

Table of Contents

• Introduction
• Discrete Planning
• Geometric Representations and Transformations
• The Configuration Space
• Sampling-Based Motion Planning
• Combinatorial Motion Planning
• Extensions of Basic Motion Planning
• Feedback Motion Planning
• Basic Decision Theory
• Sequential Decision Theory
• Sensors and Information Spaces
• Planning Under Sensing Uncertainty
• Differential Models
• Sampling-Based Planning Under Differential Constraints
• System Theory and Analytical Techniques

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