2D SLAM Algorithms Characterization, Calibration, and Comparison Considering Pose Error, Map Accuracy as Well as CPU and Memory Usage †

The present work proposes a method to characterize, calibrate, and compare, any 2D SLAM algorithm, providing strong statistical evidence, based on descriptive and inferential statistics to bring confidence levels about overall behavior of the algorithms and their comparisons. This work focuses on ch...

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Detalles Bibliográficos
Autores principales: Trejos, Kevin, Rincón, Laura, Bolaños, Miguel, Fallas, José, Marín, Leonardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506160/
https://www.ncbi.nlm.nih.gov/pubmed/36146253
http://dx.doi.org/10.3390/s22186903

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506160/
https://www.ncbi.nlm.nih.gov/pubmed/36146253
http://dx.doi.org/10.3390/s22186903

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