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UAV-BASED ACQUISITION OF 3D POINT CLOUD - A COMPARISON OF A LOW-COST LASER SCANNER AND SFM-TOOLS

机译:基于UAV的3D点云采集 - 低成本激光扫描仪和SFM工具的比较

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The Project ADFEX (Adaptive Federative 3D Exploration of Multi Robot System) pursues the goal to develop a time- and cost-efficient system for exploration and monitoring task of unknown areas or buildings. A fleet of unmanned aerial vehicles equipped with appropriate sensors (laser scanner, RGB camera, near infrared camera, thermal camera) were designed and built. A typical operational scenario may include the exploration of the object or area of investigation by an UAV equipped with a laser scanning range finder to generate a rough point cloud in real time to provide an overview of the object on a ground station as well as an obstacle map. The data about the object enables the path planning for the robot fleet. Subsequently, the object will be captured by a RGB camera mounted on the second flying robot for the generation of a dense and accurate 3D point cloud by using of structure from motion techniques. In addition, the detailed image data serves as basis for a visual damage detection on the investigated building. This paper focuses on our experience with use of a low-cost light-weight Hokuyo laser scanner onboard an UAV. The hardware components for laser scanner based 3D point cloud acquisition are discussed, problems are demonstrated and analyzed, and a quantitative analysis of the accuracy potential is shown as well as in comparison with structure from motion-tools presented.
机译:项目ADFEX(多机器人系统的自适应联合3D勘探)追求了开发时间和成本高效的探索和监测未知区域或建筑物的任务。设计并建造了一批配备适当的传感器(激光扫描仪,RGB相机,近红外摄像机,热摄像机)的无人驾驶飞行器。典型的操作场景可以包括通过配备有激光扫描范围查找器的无人机对象或调查区域的探索,以实时生成粗点云,以提供地面站上的物体以及障碍物的概述地图。关于该对象的数据启用了机器人舰队的路径规划。随后,将通过安装在第二飞行机器人上的RGB摄像机捕获对象,用于通过使用来自运动技术的结构来产生密集和精确的3D点云。另外,详细的图像数据是对研究建筑物的视觉损伤检测的基础。本文侧重于我们使用低于无人机的低成本轻型Hokuyo激光扫描仪的经验。讨论了基于激光扫描仪的3D点云采集的硬件组件,证明和分析了问题,并显示了对精度电位的定量分析,以及与所呈现的运动工具的结构相比。

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