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LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

机译：低空遥感和网络传感器数据采集中的LiDAR增强型无人机最优路径规划

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摘要

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.
机译：本技术报告介绍了一种用于低空飞行方法的光检测和测距（LiDAR）增强的最佳路径规划方法，用于遥感和采样无人机（UAV）。该无人机用于从地面传感器网络执行远程空气采样和数据采集。包含地形信息的数据以3D点云图的形式被算法处理以找到最佳路径。结果表明，该方法和算法能够在计划从起点到目标点的路径时使用LiDAR数据来避免障碍。该报告比较了LIDAR地图分辨率提高和包括数字高程模型（DEM）时该方法的性能。从实际的角度来看，最佳路径计划已加载并似乎可以与无人机地面站一起工作，并且还显示了无人机地面站软件，其中增加了更准确的LIDAR数据。

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    Leong Yue;

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  • 年度 2012
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