@inproceedings{3e4c19ee996143f0b22641bf54aa3a9c,
title = "Compressed Unscented Kalman filter-based SLAM",
abstract = "This paper proposes a real-time nonlinear filtering approach for the SLAM problem, termed as compressed Unscented Kalman filter (CUKF). A partial sampling strategy was recently proposed to make the computational complexity of the UKF quadratic with the state-vector dimension. However, the quadratic complexity remains intractable for the large-scale SLAM. To address this problem, we firstly prove the equivalence of the partial and full sampling strategies for the decoupled nonlinear system. Then a compressed form is presented by reformulating the cross-correlation items. Finally, experimental results based on simulated and practical datasets validate the effectiveness of the proposed approach.",
keywords = "Computational Complexity, Partial Sampling, SLAM, Unscented Kalman Filter",
author = "Jiantong Cheng and Jonghyuk Kim and Zhenyu Jiang and Xixiang Yang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014 ; Conference date: 05-12-2014 Through 10-12-2014",
year = "2014",
month = apr,
day = "20",
doi = "10.1109/ROBIO.2014.7090563",
language = "English",
series = "2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1602--1607",
booktitle = "2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014",
address = "United States",
}