Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively...

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Detalles Bibliográficos
Autores principales: He, Bo, Liu, Yang, Dong, Diya, Shen, Yue, Yan, Tianhong, Nian, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570400/
https://www.ncbi.nlm.nih.gov/pubmed/26287194
http://dx.doi.org/10.3390/s150819852

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570400/
https://www.ncbi.nlm.nih.gov/pubmed/26287194
http://dx.doi.org/10.3390/s150819852

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