DocumentCode :
250655
Title :
Multi channel generalized-ICP
Author :
Servos, James ; Waslander, S.L.
Author_Institution :
Univ. of Waterloo, Waterloo, ON, Canada
fYear :
2014
fDate :
May 31 2014-June 7 2014
Firstpage :
3644
Lastpage :
3649
Abstract :
Current state of the art scan registration algorithms which use only position information often fall victim to correspondence ambiguity and degeneracy in the optimization solutions. Other methods which use additional channels, such as color or intensity, often use only a small fraction of the available information and ignore the underlying structural information of the added channels. The proposed method incorporates the additional channels directly into the scan registration formulation to provide information within the plane of the surface. This is achieved by calculating the uncertainty both along and perpendicular to the local surface at each point and calculating nearest neighbour correspondences in the higher dimensional space. The proposed method reduces instances of degenerate transformation estimates and improves both registration accuracy and convergence rate. The method is tested on the Ford Vision and Lidar dataset using both color and intensity channels as well as on Microsoft Kinect data obtained from the University of Waterloo campus.
Keywords :
SLAM (robots); image colour analysis; image registration; iterative methods; optimisation; color channel; convergence rate; intensity channel; iterative closest point; multichannel generalized-ICP; nearest neighbour correspondence; optimization solution; position information; scan registration algorithm; Covariance matrices; Image color analysis; Iterative closest point algorithm; Laser radar; Sensors; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
Type :
conf
DOI :
10.1109/ICRA.2014.6907386
Filename :
6907386
Link To Document :
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