Silvia Ferrari, Thomas A. Wettergren

Information-Driven Planning and Control (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: MIT Press
• Seitenzahl: 688
• Erscheinungstermin: 6. Juli 2021
• Englisch
• ISBN-13: 9780262362399
• Artikelnr.: 60112957

Autorenporträt

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.

Inhaltsangabe

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