A HYBRID SENSING APPROACH TO MOBILE ROBOT LOCALIZATION IN COMPLEX INDOOR ENVIRONMENTS

Yan Zhuang, Ke Wang, Wei Wang, and Huosheng Hu

Keywords

Localization, hybrid metrictopological map, omnidirectional vision, laser scan matching

Abstract

This paper presents a hybrid sensing system for mobile robot localization in large-scale indoor environments. The system operates in two sensing modes, either omni-directional vision or laser scanning, according to the environmental characteristics. For a structured corridor environment, the vision information is adopted to track the robot pose with a predefined hybrid metric-topological map. For a semi-structured office room, the laser scanning mode is chosen to generate a sequence of relative pose transformations based on a scan matching algorithm. Kalman filters are deployed to smooth multiple scan matching results. The proposed hybrid sensing system can perform localization tasks on-the-fly, with the features of efficient map modelling and computational simplicity. Experimental results are provided to demonstrate the performance and effectiveness of the proposed techniques.

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