TY - GEN
T1 - A novel mobile robot localization method via finite memory filtering based on refined measurement
AU - Lee, Sang Su
AU - Lee, Dhong Hun
AU - Lee, Dong Kyu
AU - Kang, Hyun Ho
AU - Ahn, Choon Ki
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - In this paper, we propose a new robot localization method for wireless sensor networks (WSNs). The proposed localization method, finite memory filtering based localization (FMFL), considers the refined measurement estimates pose of a mobile robot, unlike existing estimators that use an infinite impulse response (IIR) structure. We design an estimator to minimize the Frobenius norm of the gain matrices to give it high robustness. The method shows excellent performance in environments, where noise information is unknown and in which sudden disturbances are inserted. Moreover, even when the observation is temporarily impossible due to the non-line-of-sight (NLOS) situation or the temporary failure of sensors, the proposed localization scheme still ensures high robustness, unlike existing methods. The performance of the proposed method is experimentally compared with existing methods in a harsh environment.
AB - In this paper, we propose a new robot localization method for wireless sensor networks (WSNs). The proposed localization method, finite memory filtering based localization (FMFL), considers the refined measurement estimates pose of a mobile robot, unlike existing estimators that use an infinite impulse response (IIR) structure. We design an estimator to minimize the Frobenius norm of the gain matrices to give it high robustness. The method shows excellent performance in environments, where noise information is unknown and in which sudden disturbances are inserted. Moreover, even when the observation is temporarily impossible due to the non-line-of-sight (NLOS) situation or the temporary failure of sensors, the proposed localization scheme still ensures high robustness, unlike existing methods. The performance of the proposed method is experimentally compared with existing methods in a harsh environment.
UR - http://www.scopus.com/inward/record.url?scp=85076748695&partnerID=8YFLogxK
U2 - 10.1109/SMC.2019.8914296
DO - 10.1109/SMC.2019.8914296
M3 - Conference contribution
AN - SCOPUS:85076748695
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 45
EP - 50
BT - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
Y2 - 6 October 2019 through 9 October 2019
ER -