{"product_id":"informationdriven-planning-and-control-isbn-9780262045421","title":"Information-Driven Planning and Control","description":"\u003cb\u003eA unified framework for developing planning and control algorithms for active sensing, with examples of applications for specific sensor technologies.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eActive 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.List of Figures xi\u003cbr\u003eList of Tables xxiii\u003cbr\u003eForeword xxv\u003cbr\u003ePreface xxvii\u003cbr\u003eI Mathematics of Information-Driven Planning and Control 1\u003cbr\u003e1 Dynamic Systems 5\u003cbr\u003e2 Optimal Control 29\u003cbr\u003e3 Graph Theory 43\u003cbr\u003e4 Probability Theory 53\u003cbr\u003e5 Information Theory 91\u003cbr\u003e6 Part I Glossary\u003cbr\u003eII Sensor System Modeling 109\u003cbr\u003e7 Mobile Platform Models 113\u003cbr\u003e8 Target Models 147\u003cbr\u003e9 Sensor Models 169\u003cbr\u003e10 Models of Environmental Variability 219\u003cbr\u003e11 Part II Glossary 231\u003cbr\u003eIII Sensing Performance and Objective Functions 235\u003cbr\u003e12 Coverage 241\u003cbr\u003e13 Detection 265\u003cbr\u003e14 Classification 293\u003cbr\u003e15 Tracking and Localization 305\u003cbr\u003e16 Part III Glossary 347\u003cbr\u003eIV Information-Driven Placement and Optimization 351\u003cbr\u003e17 Packing Algorithms 357\u003cbr\u003e18 Voronoi Diagrams 371\u003cbr\u003e19 Multi-Objective Optimization 391\u003cbr\u003e20 Metaheuristic Optimization 433\u003cbr\u003e21 Optimal Placement of Dynamic Sensors 477\u003cbr\u003e22 Part IV Glossary 489\u003cbr\u003eV Information-Driven Planning and Control Methods\u003cbr\u003e23 Sensor Trajectory Optimization 499\u003cbr\u003e24 Sensor Path Planning 515\u003cbr\u003e25 Integrated Sensor Planning and Control 571\u003cbr\u003e26 Part V Glossary 587\u003cbr\u003eReferences 591\u003cbr\u003eContributors 623\u003cbr\u003eIndex 625Silvia Ferrari is the John Brancaccio Professor of Mechanical and Aerospace Engineering in the Sibley School of Mechanical and Aerospace Engineering at Cornell University. \u003cbr\u003e\u003cbr\u003eThomas A. Wettergren is Research Scientist in Applied Mathematics and Adjunct Professor at the University of Rhode Island.","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":46300114157797,"sku":"NP9780262045421","price":75.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780262045421.jpg?v=1767730045","url":"https:\/\/k12savings.com\/products\/informationdriven-planning-and-control-isbn-9780262045421","provider":"K12savings","version":"1.0","type":"link"}