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Accurate three-dimensional perception is a key technology for many engineering applications, including mobile mapping, obstacle detection and virtual reality. In this article, we present a hand-held embedded system designed for constructing 3D representation of structured indoor environments. Different from traditional vehicle-borne mobile mapping methods, the system presented here is capable of efficiently acquiring 3D data while an operator carrying the device traverses through the site. It consists of a simultaneous localization and mapping(SLAM) module, a 3D attitude estimate module and a point cloud processing module. The SLAM is based on a scan matching approach using a modern LIDAR system, and the 3D attitude estimate is generated by a navigation filter using inertial sensors. The hardware comprises three 2D time-flight laser range finders and an inertial measurement unit(IMU). All the sensors are rigidly mounted on a body frame. The algorithms are developed on the frame of robot operating system(ROS). The 3D model is constructed using the point cloud library(PCL). Multiple datasets have shown robust performance of the presented system in indoor scenarios.
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