State Transition for Statistical SLAM Using Planar Features in 3D Point Clouds

State Transition for Statistical SLAM Using Planar Features in 3D Point Clouds

There is a large body of literature on solving the SLAM problem for various autonomous vehicle applications. A substantial part of the solutions is formulated based on using statistical (mainly Bayesian) filters such as Kalman filter and its extended version. In such solutions, the measurements are...

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Bibliographic Details
Main Authors: Amirali Khodadadian Gostar, Chunyun Fu, Weiqin Chuah, Mohammed Imran Hossain, Ruwan Tennakoon, Alireza Bab-Hadiashar, Reza Hoseinnezhad
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Sensors
Subjects:
simultaneous localization and mapping
planar features
plane parameters
transition model
Bayesian filters
Online Access:https://www.mdpi.com/1424-8220/19/7/1614

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