@inproceedings{d15c9110cabb4cfabb90e19b513e01e6,
title = "Factor graph based incremental smoothing in inertial navigation systems",
abstract = "This paper describes a new approach for information fusion in inertial navigation systems. In contrast to the commonly used filtering techniques, the proposed approach is based on a non-linear optimization for processing incoming measurements from the inertial measurement unit (IMU) and any other available sensors into a navigation solution. A factor graph formulation is introduced that allows multi-rate, asynchronous, and possibly delayed measurements to be incorporated in a natural way. This method, based on a recently developed incremental smoother, automatically determines the number of states to recompute at each step, effectively acting as an adaptive fixed-lag smoother. This yields an efficient and general framework for information fusion, providing nearly-optimal state estimates. In particular, incoming IMU measurements can be processed in real time regardless to the size of the graph. The proposed method is demonstrated in a simulated environment using IMU, GPS and stereo vision measurements and compared to the optimal solution obtained by a full non-linear batch optimization and to a conventional extended Kalman filter (EKF).",
keywords = "Navigation, factor graph, filtering, information fusion",
author = "Vadim Indelman and Stephen Williams and Michael Kaess and Frank Dellaert",
year = "2012",
language = "الإنجليزيّة",
isbn = "9780982443859",
series = "15th International Conference on Information Fusion, FUSION 2012",
pages = "2154--2161",
booktitle = "15th International Conference on Information Fusion, FUSION 2012",
note = "15th International Conference on Information Fusion, FUSION 2012 ; Conference date: 07-09-2012 Through 12-09-2012",
}