Simultaneous localization and mapping (SLAM): part II

Simultaneous localization and mapping (SLAM): part II

This paper discusses the recursive Bayesian formulation of the simultaneous localization and mapping (SLAM) problem in which probability distributions or estimates of absolute or relative locations of landmarks and vehicle pose are obtained. The paper focuses on three key areas: computational comple...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE robotics & automation magazine 2006-09, Vol.13 (3), p.108-117
Hauptverfasser: Bailey, T., Durrant-Whyte, H.
Format: Artikel
Sprache:eng
Schlagworte:
Automotive components
Bayesian methods
Computational complexity
Computational efficiency
Delay estimation
Landmarks
Localization
Mapping
Mobile robots
Position (location)
Recursive
Representations
Robotics and automation
Robustness
Simultaneous localization and mapping
Uncertainty
Vehicles
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper discusses the recursive Bayesian formulation of the simultaneous localization and mapping (SLAM) problem in which probability distributions or estimates of absolute or relative locations of landmarks and vehicle pose are obtained. The paper focuses on three key areas: computational complexity; data association; and environment representation
ISSN:1070-9932
1558-223X
DOI:10.1109/MRA.2006.1678144