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Map building and localization of mobile robots is one of the keys to implementing autonomous navigation systems. Owing to the many efforts in the past decade it has proved that map building and localization simultaneously (SLAM, simultaneous localization and map-building) is possible both theoretically and practically. Features or landmarks obtained from sensor measurements are registered and associated in SLAM if they are sustainable and correctly matched ones. To have such features it is essential to use a sensor system that provides precise range measurements. Typical sensors for SLAM are such as laser range finder (LIDAR) or ultrasonic sensors. LIDARs provide very accurate and long range measurements while measurements from ultrasonic sensors are shorter and coarse due to cone shaped beam patterns. In this paper we propose a SLAM system using a structured light sensor to SLAM in home environment. The accuracy is less than that of LIDAR (10 cm at 3 meters), but measurements are very dense laterally so that a small corners, often existing in home environments, can be determined as feature points in 3 meters. We introduce the implemented system for home use and prove its efficacy by showing the SLAM experimental results.