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Can I read Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building (Springer Tracts in Advanced Robotics (23)) on EtoBox?

Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building (Springer Tracts in Advanced Robotics (23)) by Juan Andrade Cetto, Alberto Sanfeliu is a engineering available to read on EtoBox.

What is Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building (Springer Tracts in Advanced Robotics (23)) about?

This monograph covers theoretical aspects of simultaneous localization and map building for mobile robots. These include estimation stability, nonlinear models for the propagation of uncertainties, temporal landmark compatibility, as well as issues pertaining the coupling of control and SLAM. One of the most relevant topics covered in this monograph is the theoretical formalism of partial observability in SLAM.

Who reads Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building (Springer Tracts in Advanced Robotics (23))?

It is typically read by working professionals who need an authoritative practice reference.

Common subject areas: medicine, law, business, engineering.

Author
Juan Andrade Cetto, Alberto Sanfeliu
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Published
2006
Language
EN
ISBN
9783540328483
Category
engineering
Subjects
Engineering, Mathematics, Technology
Updated
2026-03-25

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