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State Estimation for Robotics 机器人学中的状态估计 Timothy D. Barfoot 精装

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作者: Timothy D. Barfoot
出版社: Cambridge University Press
ISBN: 9781107159396

出版时间: 2008-10
装帧: 精装

作者: Timothy D. Barfoot
出版社: Cambridge University Press

ISBN: 9781107159396
出版时间: 2008-10

装帧: 精装

售价 1381.00

定价￥1381.00

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上书时间2024-03-28

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商品分类：

外文古旧书 > 英文书 > 综合性图书

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YB-71189

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A key aspect of robotics today is estimating the state, such as position and orientation, of a robot as it moves through the world. Most robots and autonomous vehicles depend on noisy data from sensors such as cameras or laser rangefinders to navigate in a three-dimensional world. This book presents common sensor models and practical advice on how to carry out state estimation for rotations and other state variables. It covers both classical state estimation methods such as the Kalman filter, as well as important modern topics such as batch estimation, the Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. The methods are demonstrated in the context of important applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Students and practitioners of robotics alike will find this a valuable resource.
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