3D Reconstruction & Assessment Framework based on affordable 2D Lidar
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Lidar is extensively used in the industry and mass market, due to its measurement accuracy and insensitivity to brightness compared to cameras. It is applied onto a broad range of applications, like geodetic engineering, self driving cars or virtual reality. But the 3D Lidar with multiple beams is very expensive, and the massive measurements data can not be fully processed timely. The purpose of this paper is to explore the possibility of using cheap 2D Lidar off-the-shelf, for 3D reconstruction with high accuracy. The 3D map quality is evaluated by our proposed metrics in this paper lastly. The 3D map is constructed in two ways, one way in which the scan is performed at known positions. The other way, in which the 2D Lidar for mapping and the localization part are placed on a trolley, then the trolley is pushed on the ground. The generated maps by these approaches are converted to octomaps before the evaluation. The similarity and difference between the two maps will be evaluated by these metrics in a normalized value ranging from 0 to 1. The established mapping system is composed of several modular components. A 3D bracket is designed for assembling the Lidar with a long range, the driver and the motor. A cover platform is designed for the imu and Lidar with a shorter range but high accuracy, which will be used to implement 2D SLAM. The software is stacked up in different packages on ROS.
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