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《Journal of Southwest University of Science and Technology》 2015-01
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Improved EKF- SLAM Method and Its Implementation on the Turtlebot

XUE Yong-sheng;WANG Heng;ZHANG Hua;HUO Jian-wen;Key Laboratories for Special Environment Robot Technology of Sichuan Province ,Southwest University of Science and Technology;  
Targeting to tackle those problems like too massive calculation,weak timeliness,low accuracy and robustness,etc.,during the process of the mobile robot 's simultaneous localization and mapping( SLAM) by using the way of the standard extended Kalman filter( EKF),combining the smoothing algorithm and singular value decomposition algorithm,a new SLAM algorithm( ERTSS- SLAM) is proposed in this paper. By the forward EKF method,the improved ERTSS- SLAM algorithm conducts the optical pose estimation of the mobile robot's odometer and gyroscopes pose information and then avoid dispersion with the standard ERTS smoother,and at the same time,the inverse calculation is prevented by using the singular value decomposition algorithm,so as to enhance the system's timeliness,robustness and accuracy accordingly. Experimental results on the Turtlebot show that the new ERTSS- SLAM algorithm is very efficient and stable during the SLAM application.
【Fund】: 四川省科技厅科技支撑计划项目(2014RZ0049);; 2014四川省科技支撑计划项目(2014GZ0021)
【CateGory Index】: TP242
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