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
Link To Document :
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