Title :
Data association technology based on multi algorithm matching for SLAM
Author :
Xingxi Shi ; Chunxia Zhao ; Tao Chen
Author_Institution :
Sch. of Sci., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
Data association is one of the critical questions to mobile robot simultaneous localization and mapping (SLAM). A data association method based on multi algorithm matching is proposed. It use equal weight particles to denote the joint probability distribution of the robot and feature map. Each of particles applies different data association algorithm and gets different data association set during SLAM, the intersecting set of all sets is taken as the objective set. The simulated experiment use the intersecting set between the NN data association set and JCBB data association set as the data association set of every step. The result shows it can effectively reduce the false data association pairs to improve the precision of robot location.
Keywords :
SLAM (robots); image fusion; image matching; mobile robots; probability; robot vision; set theory; JCBB data association set; NN data association set; SLAM; data association technology; false data association pair reduction; feature map; intersecting set; joint probability distribution; mobile robot simultaneous localization-and-mapping; multialgorithm matching; objective set; robot location precision improvement; Joints; Mobile robots; Probability distribution; Robot kinematics; Simultaneous localization and mapping; Technological innovation; data association; mobile robot; multi algorithm matching (MAM); simultaneous localization and mapping (SLAM);
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7052841