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3D Mapping Based on Fusion of 2D Laser and IMU Data Acquired by Unmanned Aerial Vehicle

机译:基于2D激光与IMU数据融合的3D映射

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The paper deals with the three-dimensional (3D) modelling based on data acquired from 2D laser sensor and IMU (Inertial Measurement Unit) attached to the UAV (Unmanned Aerial Vehicle). The used multi-sensor unit produces 2D scans and provides information about Euler angles or quaternions. These angles are used to describe the UAV orientation in 3D space, more precisely the orientation of the laser sensor. In order to generate 3D occupancy map it is necessary to rotate the laser sensor around its axis yielding the 2D scans being mapped on 3D space using quaternions. Inertial sensor and Sweep LiDAR laser measurements are transmitted to the single board computer Odroid XU4 (SBC). The data fusion was performed under ROS (Robot Operating System) installed on the SBC, producing 3D space points. These points are transmitted over the network to the central computer on which the UAV localization and mapping processes are done within the ROS. The effectiveness of the proposed system for 3D modelling of the UAV environment is verified by experiment.
机译:本文基于从2D激光传感器和连接到UAV(无人机)的IMU(惯性测量单元)获取的数据进行三维(3D)建模。使用的多传感器单元可进行2D扫描,并提供有关欧拉角或四元数的信息。这些角度用于描述3D空间中的UAV方向,更准确地说是激光传感器的方向。为了生成3D占用图,有必要使激光传感器绕其轴旋转,以产生使用四元数映射到3D空间的2D扫描。惯性传感器和扫频LiDAR激光测量结果被传输到单板计算机Odroid XU4(SBC)。数据融合是在SBC上安装的ROS(机器人操作系统)下进行的,产生3D空间点。这些点通过网络传输到中央计算机,在该中央计算机上进行ROS内的UAV定位和映射过程。实验验证了所提出系统对无人机环境进行3D建模的有效性。

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