Environment learning for indoor mobile robots : a stochastic state estimation approach to simultaneous localization and map building
Author(s)
Bibliographic Information
Environment learning for indoor mobile robots : a stochastic state estimation approach to simultaneous localization and map building
（Springer tracts in advanced robotics, v. 23）
Springer, c2006
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Note
Bibliography: p. [131]-136
Description and Table of Contents
Description
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.
Table of Contents
Simultaneous Localization and Map Building.- Marginal Filter Stability.- Suboptimal Filter Stability.- Unscented Transformation of Vehicle States.- Simultaneous Localization, Control and Mapping.- A: The Kalman Filter.- B: Concepts from Linear Algebra.- C: Sigma Points.
by "Nielsen BookData"
