<i>δ</i>-Generalized Labeled Multi-Bernoulli Simultaneous Localization and Mapping with an Optimal Kernel-Based Particle Filtering Approach

Under realistic environmental conditions, heuristic-based data association and map management routines often result in divergent map and trajectory estimates in robotic Simultaneous Localization And Mapping (SLAM). To address these issues, SLAM solutions have been proposed based on the Random Finite...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Diluka Moratuwage, Martin Adams, Felipe Inostroza
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2019-05-01
Schriftenreihe:	Sensors
Schlagworte:	SLAM robotics tracking random finite sets
Online-Zugang:	https://www.mdpi.com/1424-8220/19/10/2290
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