State Estimation for Robotics


State Estimation for Robotics
Authors: Timothy D. Barfoot
Year: 2017
Publisher: Cambridge University Press
Language: English
ISBN 13: 9781316671528
ISBN 10: 1316671526
Categories: Computers, Artificial Intelligence (AI)
Pages: 320 / 319

Availability: 5000 in stock

SKU: 9781316671528 Categories: ,

State Estimation for Robotics Timothy D. Barfoot
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. Categories:
Computers – Artificial Intelligence (AI)
Cambridge University Press
ISBN 10:
ISBN 13:
40 MB


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State Estimation for Robotics

Availability: 5000 in stock