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

<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...

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Bibliographic Details
Main Authors: Diluka Moratuwage, Martin Adams, Felipe Inostroza
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Sensors
Subjects:
SLAM
robotics
tracking
random finite sets
Online Access:https://www.mdpi.com/1424-8220/19/10/2290

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