Planning Algorithms

Inbunden, Engelska, 2006

1 445 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2006-05-29
Mått:182 x 262 x 43 mm
Vikt:1 590 g
Format:Inbunden
Språk:Engelska
Antal sidor:844
Förlag:Cambridge University Press
ISBN:9780521862059

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Mer om författaren

Steven M. LaValle is Associate Professor of Computer Science at the University of Illinois, Urbana-Champaign. He has worked in motion planning and robotics for over a decade and is a leading researcher who has published dozens of articles in the field. He is the main developer of the Rapidly-exploring Random Tree (RRT) algorithm, which has been used in numerous research labs and industrial products around the world. He has taught material on which the book is based at Stanford University, Iowa State University, the Tec de Monterrey, and the University of Illinois.

Recensioner i media

'This is a terrific book, a milestone in the robotics literature.' Matt Mason, Director of The Carnegie Mellon Robotics Institute

Innehållsförteckning

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.