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In this paper, we propose a consistency adjustment algorithm for a new localization method based on a client-server model of mobile devices such as indoor mobile robots and smart phones to realize intelligent environments. The distance of movement is calculated using feature points of consecutive images, and subsequently the range of the estimated position is reduced based on the distance. We already have developed an indoor location estimation infrastructure called Universal Map (UMap) using the pre-map. UMap generates a two-dimensional image as a database in advance. The system performs an indoor location estimation by matching the database image and the sensor image. While the maximum error in the previous scheme using only UMap was 76.11 m, the maximum error in this proposed method was reduced to 1.42 m.
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