DocumentCode :
2585341
Title :
Natural feature based localization in forested environments
Author :
Song, Meng ; Sun, Fengchi ; Iagnemma, Karl
Author_Institution :
Coll. of Software, Nankai Univ., Tianjin, China
fYear :
2012
fDate :
7-12 Oct. 2012
Firstpage :
3384
Lastpage :
3390
Abstract :
This paper presents a new feature based scan matching method for solving 6D localization problem in forested environments. The proposed registration process includes two steps. First, the largest group of approximately parallel tree trunk features is utilized to align successive scans along the five dimensions except z direction. Tree correspondences are established by matching point patterns which are abstracted from the position relationships of trees. The optimal 5D transformation is thus determined based on the axes of two key tree pairs which are selected by evaluating their ability of tree alignment. Second, we assign the ground points of two scans into a grid of cells, and minimize z-direction difference of points in shared cells. The experimental results on data collected in real forested environments have demonstrated the effectiveness of this method.
Keywords :
SLAM (robots); image matching; image registration; mobile robots; optical scanners; pose estimation; robot vision; vegetation; 5D transformation; 6D localization problem; feature based scan matching method; forested environments; matching point patterns; mobile robots; parallel tree trunk features; pose determination; pose tracking; registration process; relative localization; tree alignment; z-direction difference; Accuracy; Feature extraction; Manganese; Pattern matching; Robot kinematics; Vegetation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on
Conference_Location :
Vilamoura
ISSN :
2153-0858
Print_ISBN :
978-1-4673-1737-5
Type :
conf
DOI :
10.1109/IROS.2012.6385542
Filename :
6385542
Link To Document :
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