Timothy D. Barfoot (University of Toronto)

State Estimation for Robotics

• Gebundenes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• 2 Revised edition
• Seitenzahl: 530
• Erscheinungstermin: 20. Dezember 2023
• Englisch
• Abmessung: 260mm x 183mm x 33mm
• Gewicht: 1170g
• ISBN-13: 9781009299893
• ISBN-10: 1009299891
• Artikelnr.: 68887606

Autorenporträt

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.

Inhaltsangabe

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.