A key aspect of robotics today is estimating the state (e.g., position and orientation) of a robot, based on noisy sensor data. This book targets students and practitioners of robotics by presenting classical state estimation methods (e.g., the Kalman filter) but also important modern topics such as batch estimation, Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. Since most robots operate in a three-dimensional world, common sensor models (e.g., camera, laser rangefinder) are provided followed by practical advice on how to carry out state estimation for rotational state variables. The book covers robotic applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Highlights of this expanded second edition include a new chapter on variational inference, a new section on inertial navigation, more introductory material on probability, and a primer on matrix calculus.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Da: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condizione: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Codice articolo 1009299891-8-1
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 46502423-n
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. A key aspect of robotics today is estimating the state (e.g., position and orientation) of a robot, based on noisy sensor data. This book targets students and practitioners of robotics by presenting classical state estimation methods (e.g., the Kalman filter) but also important modern topics such as batch estimation, Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. Since most robots operate in a three-dimensional world, common sensor models (e.g., camera, laser rangefinder) are provided followed by practical advice on how to carry out state estimation for rotational state variables. The book covers robotic applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Highlights of this expanded second edition include a new chapter on variational inference, a new section on inertial navigation, more introductory material on probability, and a primer on matrix calculus. This book is intended for students and practitioners of robotics working with noisy sensor data to estimate state variables. New edition highlights include a new chapter on variational inference and new sections on adaptive covariance estimation and on inertial navigation as well as a primer on matrix calculus. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781009299893
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26398669850
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 46502423
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Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781009299893_new
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Codice articolo 397707205
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Da: Chiron Media, Wallingford, Regno Unito
Hardcover. Condizione: New. Codice articolo 6666-GRD-9781009299893
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 2nd edition. 581 pages. 10.00x7.00x1.13 inches. In Stock. Codice articolo __1009299891
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 46502423-n
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