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.File in questo prodotto:
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