Paper Info
Title
Simultaneous Localization and Mapping with a Dynamic Switching Mechanism (SLAM-DSM)
Abstract
In this paper, we propose a simultaneous localization and mapping (SLAM) algorithm incorporating a dynamic switching mechanism to switch between FastSLAM 1.0 and 2.0, based on a threshold of effective sample size (ESS). By taking advantages of FastSLAM 1.0 and 2.0 through the proposed dynamic switching mechanism, execution efficiency is significantly improved while maintaining an acceptable accuracy of estimations. To show the effectiveness of our proposed approach in comparison to FastSLAM 1.0 and 2.0, several simulations are demonstrated in this paper.
Year
DOI
Venue
2015
10.1007/978-3-319-31293-4_5
ROBOT INTELLIGENCE TECHNOLOGY AND APPLICATIONS 4
Keywords
Field
DocType
FastSlam,Particle filter,Extended Kalman filter
Extended Kalman filter,Alpha beta filter,Fast Kalman filter,Control theory,Computer science,Particle filter,Dynamic switching,Moving horizon estimation,Simultaneous localization and mapping,Effective sample size
Conference
Volume
ISSN
Citations 
447
2194-5357
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Chun-Hsiao Yeh100.34
Herng-Hua Chang29413.07
Chen-Chien James Hsu33811.17
Wei-Yen Wang499587.40