DocumentCode :
2420976
Title :
Incremental probabilistic geometry estimation for robot scene understanding
Author :
Cahier, Louis-Kenzo ; Ogata, Tetsuya ; Okuno, Hiroshi G.
Author_Institution :
Grad. Sch. of Inf., Univ. of Kyoto, Kyoto, Japan
fYear :
2012
fDate :
14-18 May 2012
Firstpage :
3625
Lastpage :
3630
Abstract :
Our goal is to give mobile robots a rich representation of their environment as fast as possible. Current mapping methods such as SLAM are often sparse, and scene reconstruction methods using tilting laser scanners are relatively slow. In this paper, we outline a new method for iterative construction of a geometric mesh using streaming time-of-flight range data. Our results show that our algorithm can produce a stable representation after 6 frames, with higher accuracy than raw time-of-flight data.
Keywords :
SLAM (robots); computational geometry; image representation; iterative methods; mesh generation; mobile robots; optical scanners; service robots; SLAM; geometric mesh; incremental probabilistic geometry estimation; iterative construction; mapping methods; mobile robots; robot scene understanding; scene reconstruction methods; service robots; streaming time-of-flight range data; tilting laser scanners; Cameras; Optical imaging; Probabilistic logic; Simultaneous localization and mapping; Surface reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
ISSN :
1050-4729
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ICRA.2012.6225343
Filename :
6225343
Link To Document :
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