Timothy D. Barfoot is a Professor at the University of Toronto Institute for Aerospace Studies (UTIAS). He has been conducting research in the area of navigation of mobile robotics for over fifteen years, both in industry and academia, for applications including space exploration, mining, military, and transportation. He has made contributions in the area of localization, mapping, planning, and control. He sits on the editorial boards of the International Journal of Robotics Research and the Journal of Field Robotics, and was the General Chair of Field and Service Robotics 2015, which was held in Toronto.
Inhaltsangabe
1. Introduction Part I. Estimation Machinery: 2. Primer on probability theory 3. Linear-Gaussian estimation 4. Nonlinear non-Gaussian estimation 5. Biases, correspondences, and outliers Part II. Three-Dimensional Machinery: 6. Primer on three-dimensional geometry 7. Matrix lie groups Part III. Applications: 8. Pose estimation problems 9. Pose-and-point estimation problems 10. Continuous-time estimation.
1. Introduction Part I. Estimation Machinery: 2. Primer on probability theory 3. Linear-Gaussian estimation 4. Nonlinear non-Gaussian estimation 5. Biases, correspondences, and outliers Part II. Three-Dimensional Machinery: 6. Primer on three-dimensional geometry 7. Matrix lie groups Part III. Applications: 8. Pose estimation problems 9. Pose-and-point estimation problems 10. Continuous-time estimation.
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