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Information-Driven Planning and Control

Silvia Ferrari Thomas A. Wettergren

$150

Hardback

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English
MIT Press
03 August 2021
A unified framework for developing planning and control algorithms for active sensing, with examples of applications for specific sensor technologies.

A unified framework for developing planning and control algorithms for active sensing, with examples of applications for specific sensor technologies.

Active sensor systems, increasingly deployed in such applications as unmanned vehicles, mobile robots, and environmental monitoring, are characterized by a high degree of autonomy, reconfigurability, and redundancy. This book is the first to offer a unified framework for the development of planning and control algorithms for active sensing, with examples of applications for a range of specific sensor technologies. The methods presented can be characterized as information-driven because their goal is to optimize the value of information, rather than to optimize traditional guidance and navigation objectives.
By:   ,
Imprint:   MIT Press
Country of Publication:   United States
Dimensions:   Height: 299mm,  Width: 178mm, 
Weight:   567g
ISBN:   9780262045421
ISBN 10:   0262045427
Series:   Cyber Physical Systems Series
Pages:   552
Publication Date:  
Audience:   General/trade ,  ELT Advanced
Format:   Hardback
Publisher's Status:   Active
List of Figures xi List of Tables xxiii Foreword xxv Preface xxvii I Mathematics of Information-Driven Planning and Control 1 1 Dynamic Systems 5 2 Optimal Control 29 3 Graph Theory 43 4 Probability Theory 53 5 Information Theory 91 6 Part I Glossary II Sensor System Modeling 109 7 Mobile Platform Models 113 8 Target Models 147 9 Sensor Models 169 10 Models of Environmental Variability 219 11 Part II Glossary 231 III Sensing Performance and Objective Functions 235 12 Coverage 241 13 Detection 265 14 Classification 293 15 Tracking and Localization 305 16 Part III Glossary 347 IV Information-Driven Placement and Optimization 351 17 Packing Algorithms 357 18 Voronoi Diagrams 371 19 Multi-Objective Optimization 391 20 Metaheuristic Optimization 433 21 Optimal Placement of Dynamic Sensors 477 22 Part IV Glossary 489 V Information-Driven Planning and Control Methods 23 Sensor Trajectory Optimization 499 24 Sensor Path Planning 515 25 Integrated Sensor Planning and Control 571 26 Part V Glossary 587 References 591 Contributors 623 Index 625

Silvia Ferrari is the John Brancaccio Professor of Mechanical and Aerospace Engineering in the Sibley School of Mechanical and Aerospace Engineering at Cornell University. Thomas A. Wettergren is Research Scientist in Applied Mathematics and Adjunct Professor at the University of Rhode Island.

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