TY - GEN
T1 - Scan-matching based 6dof slam using omnidirectional stereo
AU - Koyasu, Hiroshi
AU - Maekawa, Hitoshi
AU - Kawasaki, Hiroshi
AU - Ono, Shintaro
AU - Ikeuchi, Katsushi
N1 - Funding Information:
This work was partly supported by JSPS KAKENHI Grant Number 23611006.
Publisher Copyright:
© 2013; MVA Organization. All rights reserved.
PY - 2013
Y1 - 2013
N2 - Simultaneous localization and mapping (SLAM) of working environments is one of the important problems in mobile robotics. For the problem, we present a new method using an omnidirectional stereo system. By using 3D range information obtained from the omnidirectional stereo, we construct scan-matching based extended Kalman filter SLAM(EKF-SLAM) system. In the system, the output of the piecewise iterative closest point(ICP) algorithm is used as the observation of the EKF. The global consistency of the robot trajectory is kept by a loop closing method based on the Kalman smoothing. Experimental results of the method are shown for a simulated environment.
AB - Simultaneous localization and mapping (SLAM) of working environments is one of the important problems in mobile robotics. For the problem, we present a new method using an omnidirectional stereo system. By using 3D range information obtained from the omnidirectional stereo, we construct scan-matching based extended Kalman filter SLAM(EKF-SLAM) system. In the system, the output of the piecewise iterative closest point(ICP) algorithm is used as the observation of the EKF. The global consistency of the robot trajectory is kept by a loop closing method based on the Kalman smoothing. Experimental results of the method are shown for a simulated environment.
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M3 - Conference contribution
AN - SCOPUS:85083075955
SN - 9784901122139
T3 - Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
SP - 306
EP - 310
BT - Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PB - MVA Organization
T2 - 13th IAPR International Conference on Machine Vision Applications, MVA 2013
Y2 - 20 May 2013 through 23 May 2013
ER -