DocumentCode
2651429
Title
A hybrid filtering and Maximum Likelihood approach to SLAM
Author
Conte, Francesco ; Martinelli, Agostino
Author_Institution
Dipt. di Ing. Elettr. e dell´´Inf., Univ. degli Studi dell´´Aquila, L´´Aquila, Italy
fYear
2010
fDate
14-18 Dec. 2010
Firstpage
803
Lastpage
809
Abstract
This paper introduces a new approach to SLAM which combines an Information Filter and a non linear optimizer. The basic idea of the suggested technique is to use the Information Filter when the system non linearities are negligible, and to switch to the use of the non linear optimizer when the non linearities are not negligible. Extensive simulations are provided in order to evaluate the performance of the proposed approach. In particular, a comparison with the Exactly Sparse Delayed-state Filers (ESDF) technique is carried out.
Keywords
SLAM (robots); filtering theory; information filters; maximum likelihood estimation; mobile robots; SLAM; exactly sparse delayed-state filers technique; filtering approach; information filter; maximum likelihood approach; nonlinear optimizer; Cost function; Estimation; Information filters; Linearity; Robot kinematics; Simultaneous localization and mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Biomimetics (ROBIO), 2010 IEEE International Conference on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-9319-7
Type
conf
DOI
10.1109/ROBIO.2010.5723429
Filename
5723429
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