TY - GEN
T1 - Scan likelihood evaluation in FastSLAM using binary Bayes filter
AU - Choi, Hyukdoo
AU - Kim, Euntai
AU - Yang, Gwang Woong
PY - 2013
Y1 - 2013
N2 - FastSLAM is a fundamental algorithm for Simultaneous Localization and Mapping (SLAM). FastSLAM based on grid map is a popular method to build a map of both the structured and unstructured environment. The performance of FastSLAM significantly depends on evaluation of measurement likelihood. In this paper, we propose a new method to evaluate laser scan likelihood using the binary Bayes filter. This method supports the right particles but does not suffer from particle depletion problem. We implemented the hardware system based on the Pioneer 2-DX platform equipped with the Hokuyo laser scanner. The experimental result shows that the proposed method builds the map accurately.
AB - FastSLAM is a fundamental algorithm for Simultaneous Localization and Mapping (SLAM). FastSLAM based on grid map is a popular method to build a map of both the structured and unstructured environment. The performance of FastSLAM significantly depends on evaluation of measurement likelihood. In this paper, we propose a new method to evaluate laser scan likelihood using the binary Bayes filter. This method supports the right particles but does not suffer from particle depletion problem. We implemented the hardware system based on the Pioneer 2-DX platform equipped with the Hokuyo laser scanner. The experimental result shows that the proposed method builds the map accurately.
UR - http://www.scopus.com/inward/record.url?scp=84888189484&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84888189484&partnerID=8YFLogxK
U2 - 10.1109/IVMSPW.2013.6611891
DO - 10.1109/IVMSPW.2013.6611891
M3 - Conference contribution
AN - SCOPUS:84888189484
SN - 9781467358583
T3 - 2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings
BT - 2013 IEEE 11th IVMSP Workshop
T2 - 2013 IEEE 11th Workshop on 3D Image/Video Technologies and Applications, IVMSP 2013
Y2 - 10 June 2013 through 12 June 2013
ER -