計画アルゴリズム<br>Planning Algorithms

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計画アルゴリズム
Planning Algorithms

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  • 製本 Hardcover:ハードカバー版／ページ数 844 p.
  • 言語 ENG
  • 商品コード 9780521862059
  • DDC分類 006.31

基本説明

A coherent source for applications including robotics, computational biology, graphics, manufacturing, aerospace, and medicine. The first broad unification of planning-related topics, drawn together under a clearly explained mathematical framework. Emphasizes the powerful concept of information spaces, critical in the development of better robotic systems.

Full Description

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning, but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the 'configuration spaces' of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. This text and reference is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Contents

Part I. Introductory Material: 1. Introduction; 2. Discrete planning; Part II. Motion Planning: 3. Geometric representations and transformations; 4. The configuration space; 5. Sampling-based motion planning; 6. Combinatorial motion planning; 7. Extensions of basic motion planning; 8. Feedback motion planning; Part III. Decision-Theoretic Planning: 9. Basic decision theory; 10. Sequential decision theory; 11. Information spaces; 12. Planning under sensing uncertainty; Part IV. Planning Under Differential Constraints: 13. Differential models; 14. Sampling-based planning under differential constraints; 15. System theory and analytical techniques.