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.

A hybrid filtering and maximum likelihood approach to SLAM

Conte, Francesco;
2010-01-01

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.
2010
9781424493173
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/872093
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