Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/7367
Title: A robust extended H∞ filtering approach to multi-robot cooperative localization in dynamic indoor environments
Authors: Zhuang, Y
Wang, Z
Yu, H
Wang, W
Lauria, S
Keywords: Multi-robot cooperative localization;Robust extended H∞ filtering (REHF);Metric-based Iterative Closest Point (MbICP);Laser data interaction
Issue Date: 2013
Publisher: Elsevier
Citation: Control Engineering Practice, 21(7): 953 - 961, Jul 2013
Abstract: Multi-robot cooperative localization serves as an essential task for a team of mobile robots to work within an unknown environment. Based on the real-time laser scanning data interaction, a robust approach is proposed to obtain optimal multi-robot relative observations using the Metric-based Iterative Closest Point (MbICP) algorithm, which makes it possible to utilize the surrounding environment information directly instead of placing a localization-mark on the robots. To meet the demand of dealing with the inherent non-linearities existing in the multi-robot kinematic models and the relative observations, a robust extended H∞ filtering (REHF) approach is developed for the multi-robot cooperative localization system, which could handle non-Gaussian process and measurement noises with respect to robot navigation in unknown dynamic scenes. Compared with the conventional multi-robot localization system using extended Kalman filtering (EKF) approach, the proposed filtering algorithm is capable of providing superior performance in a dynamic indoor environment with outlier disturbances. Both numerical experiments and experiments conducted for the Pioneer3-DX robots show that the proposed localization scheme is effective in improving both the accuracy and reliability of the performance within a complex environment.
Description: This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2013 Elsevier.
URI: http://www.sciencedirect.com/science/article/pii/S0967066113000245
http://bura.brunel.ac.uk/handle/2438/7367
DOI: http://dx.doi.org/10.1016/j.conengprac.2013.02.006
ISSN: 0967-0661
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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