Environment Learning for Indoor Mobile Robots : A Stochastic State Estimation Approach to Simultaneous Localization and Map Building
This monograph covers theoretical aspects of simultaneous localization and map building for mobile robots, such as 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 m...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2006.
Cham : Springer Nature |
| Serier: | Springer Tracts in Advanced Robotics
23 |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Environment Learning for Indoor Mobile Robots, Texte imprimé, 9783642069314 • Environment Learning for Indoor Mobile Robots, Texte imprimé, 9783540821373 • Environment Learning for Indoor Mobile Robots, Texte imprimé, 9783540327950 |
Indholdsfortegnelse:
- 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.