TY - GEN
T1 - Indoor Localization for Mobile Robots Using Odometry and Vision System
T2 - 5th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2018
AU - Li, Wenling
AU - Zheng, Wenhao
AU - Liu, Yang
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/10
Y1 - 2018/12/10
N2 - This paper studies the problem of indoor localization for mobile robots using odometry and vision system. As the odometry adopts a higher sampling rate than the camera, a pseudo measurement approach is proposed to recover the visual measurements such that the position of the mobile robot can be estimated by the visual measurements with the same sampling rate of the odometry. To improve the robustness with respect to measurement variations, a self-tuning parameter is introduced in the pseudo measurement and the normalized least mean square algorithm is used to adjust the self-tuning parameter adaptively. By formulating the localization problem in the framework of Bayesian estimation, the unscented Kalman filter is utilized to handle the nonlinear filtering problem. Experimental results are provided to illustrate the effectiveness of the proposed approach.
AB - This paper studies the problem of indoor localization for mobile robots using odometry and vision system. As the odometry adopts a higher sampling rate than the camera, a pseudo measurement approach is proposed to recover the visual measurements such that the position of the mobile robot can be estimated by the visual measurements with the same sampling rate of the odometry. To improve the robustness with respect to measurement variations, a self-tuning parameter is introduced in the pseudo measurement and the normalized least mean square algorithm is used to adjust the self-tuning parameter adaptively. By formulating the localization problem in the framework of Bayesian estimation, the unscented Kalman filter is utilized to handle the nonlinear filtering problem. Experimental results are provided to illustrate the effectiveness of the proposed approach.
UR - https://www.scopus.com/pages/publications/85060279642
U2 - 10.1109/ICCSS.2018.8572305
DO - 10.1109/ICCSS.2018.8572305
M3 - 会议稿件
AN - SCOPUS:85060279642
T3 - 2018 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2018
SP - 457
EP - 462
BT - 2018 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 August 2018 through 19 August 2018
ER -