DocumentCode :
3006843
Title :
AMCL based map fusion for multi-robot SLAM with heterogenous sensors
Author :
Baoxian Zhang ; Jun Liu ; Haoyao Chen
Author_Institution :
Shenzhen Grad. Sch., Dept. of Mech. Eng. & Autom., Harbin Inst. of Technol., Shenzhen, China
fYear :
2013
fDate :
26-28 Aug. 2013
Firstpage :
822
Lastpage :
827
Abstract :
This paper proposes an efficient adaptive Monte Carlo Localization (AMCL) based approach to align the occupancy grid maps built by a multi-robot system. Map alignment plays an important role for the map fusion of multi-robot simultaneous localization and mapping (SLAM), especially for the SLAM with heterogenous sensors. Two robots equipped with a laser and Kinect respectively are executing FastSLAM 2.0 in the same environment but at different starting point; the motion and measurement information is recorded with time-stamps. To merge the maps built by different robots, one robot is first relocated in the map built by the other robot by using the recorded motion sequences and measurement information. With the relocation result, the transformation matrix between the two different maps is the calculated; the matrix is further used as the initial relative pose information for ICP process to obtain precise alignment result. Experiments are finally performed to demonstrate the effectiveness of the proposed approach. Index Terms - AMCL; map fusion; multi-robot SLAM; heterogenous sensors.
Keywords :
Monte Carlo methods; SLAM (robots); image fusion; image motion analysis; image sequences; matrix decomposition; multi-robot systems; pose estimation; sensors; AMCL based approach; AMCL based map fusion; FastSLAM 2.0; ICP process; adaptive Monte Carlo localization; heterogenous sensors; map alignment; measurement information; motion information; multirobot SLAM; multirobot simultaneous localization and mapping; multirobot system; occupancy grid maps; precise alignment; recorded motion sequences; relative pose information; time-stamps; transformation matrix; Iterative closest point algorithm; Laser fusion; Robot kinematics; Simultaneous localization and mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2013 IEEE International Conference on
Conference_Location :
Yinchuan
Type :
conf
DOI :
10.1109/ICInfA.2013.6720407
Filename :
6720407
Link To Document :
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