A robust extended H-infinity filtering approach to multi-robot cooperative localization in dynamic indoor environments

作者：Zhuang, Yan; Wang, Zidong^*; Yu, Haiyang; Wang, Wei; Lauria, Stanislao

来源：Control Engineering Practice, 2013, 21(7): 953-961.

DOI：10.1016/j.conengprac.2013.02.006

• Multi-robot cooperative localization
• Robust extended H-infinity filtering (REHF)
• Metric-based Iterative Closest Point (MbICP)
• Laser data interaction

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-infinity 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.

• 出版日期2013-7
• 单位大连理工大学