An Extended Kalman Filter for Magnetic Field SLAM Using Gaussian Process Regression

We present a computationally efficient algorithm for using variations in the ambient magnetic field to compensate for position drift in integrated odometry measurements (dead-reckoning estimates) through simultaneous localization and mapping (SLAM). When the magnetic field map is represented with a...

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Detalles Bibliográficos
Autores principales: Viset, Frida, Helmons, Rudy, Kok, Manon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025971/
https://www.ncbi.nlm.nih.gov/pubmed/35458817
http://dx.doi.org/10.3390/s22082833

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025971/
https://www.ncbi.nlm.nih.gov/pubmed/35458817
http://dx.doi.org/10.3390/s22082833

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