ACK-MSCKF: Tightly-Coupled Ackermann Multi-State Constraint Kalman Filter for Autonomous Vehicle Localization

Visual-Inertial Odometry (VIO) is subjected to additional unobservable directions under the special motions of ground vehicles, resulting in larger pose estimation errors. To address this problem, a tightly-coupled Ackermann visual-inertial odometry (ACK-MSCKF) is proposed to fuse Ackermann error st...

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Detalles Bibliográficos
Autores principales: Ma, Fangwu, Shi, Jinzhu, Yang, Yu, Li, Jinhang, Dai, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864737/
https://www.ncbi.nlm.nih.gov/pubmed/31694304
http://dx.doi.org/10.3390/s19214816

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864737/
https://www.ncbi.nlm.nih.gov/pubmed/31694304
http://dx.doi.org/10.3390/s19214816

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