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Local map update for large scale SLAM

A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation

IEEE

Autor: Aulinas Masó, Josep M.
Salvi, Joaquim
Lladó Bardera, Xavier
Petillot, Yvan R.
Resum: A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation
Accés al document: http://hdl.handle.net/2072/58620
Llenguatge: eng
Editor: IEEE
Drets: Tots els drets reservats
Matèria: Algorismes computacionals
Imatges -- Processament
Processos estocàstics
Computer algorithms
Image processing
Stochastic processes
Títol: Local map update for large scale SLAM
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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