
State Estimation for Robotics
Second Edition
Timothy D. Barfoot(Author)
Cambridge University Press
2nd Edition
Published on 1. February 2024
Book
Hardback
530 pages
978-1-009-29989-3 (ISBN)
Description
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.
Reviews / Votes
'This book provides a timely, concise, and well-scoped introduction to state estimation for robotics. It complements existing textbooks by giving a balanced presentation of estimation theoretic and geometric tools and discusses how these tools can be used to solve common estimation problems arising in robotics. It also strikes an excellent balance between theory and motivating examples.' Luca Carlone, IEEE Control Systems MagazineMore details
Edition
2nd Revised edition
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Edition type
Revised edition
Illustrations
Worked examples or Exercises
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 33 mm
Weight
1181 gr
ISBN-13
978-1-009-29989-3 (9781009299893)
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Schweitzer Classification
Other editions
Additional editions

E-Book
01/2024
2nd Edition
Cambridge University Press
€86.49
Available for download
Previous edition

Timothy D. Barfoot
State Estimation for Robotics
Book
07/2017
Cambridge University Press
€111.50
Article exhausted; check for reprint
Person
Timothy D. Barfoot is a Professor at the University of Toronto Institute for Aerospace Studies. He has been conducting research in the area of navigation of mobile robotics for over 20 years, both in industry and academia, for applications including space exploration, mining, military, and transportation. He is a Fellow of the IEEE Robotics and Automation Society.
Content
Acronyms and abbreviations; Notation; Foreword to first edition; Foreword to second edition; 1. Introduction; Part I. Estimation Machinery: 2. Primer on probability theory; 3. Linear-Gaussian estimation; 4. Nonlinear non-Gaussian estimation; 5. Handling nonidealities in estimation; 6. Variational inference; Part II. Three-Dimensional Machinery: 7. Primer on three-dimensional geometry; 8. Matrix lie groups; Part III. Applications: 9. Pose estimation problems; 10. Pose-and-point estimation problems; 11. Continuous-time estimation; Appendix A: matrix primer; Appendix B: rotation and pose extras; Appendix C: miscellaneous extras; Appendix D: solutions to exercises; References; Index.