DocumentCode
3587112
Title
A novel fusion method for robot indoor environment mapping
Author
Huo Guanglei ; Li Ruifeng ; Zhao Lijun ; Wang Ke
Author_Institution
State Key Lab. of Robot. & Syst., Harbin Inst. of Technol., Harbin, China
fYear
2014
Firstpage
2507
Lastpage
2510
Abstract
In order to solve the stability of mapping of mobile robot, a fusion method based on Kalman Filter is proposed to reduce the accumulative errors during the mobile motion. This fusion method, which can fuse the sequential scan matching results and odometer measures, is suitable for raw points based scan matching method. In this paper, pose estimation results from raw points based scan matching method are viewed as the observation model, and odometer measures are viewed as the status model. Experimental results are shown to validate the effectiveness of the proposed approach.
Keywords
Kalman filters; SLAM (robots); distance measurement; indoor environment; mobile robots; sensor fusion; Kalman filter; accumulative error reduction; fusion method; mobile motion; mobile robot mapping stability; observation model; odometer measures; pose estimation; raw point based scan matching method; robot indoor environment mapping; sequential scan matching; status model; Estimation; Iterative closest point algorithm; Mobile robots; Robot kinematics; Simultaneous localization and mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
Type
conf
DOI
10.1109/ROBIO.2014.7090717
Filename
7090717
Link To Document