基于SLAM的无人机飞行参数设定方法研究#br#

为克服无人机林间飞行环境复杂、作业多样化、点云数据质量难以评价等导致的飞行参数不合理、点云数据质量差的问题，提出一种基于同时定位与建图(Simultaneous Localization and Mapping，SLAM)的无人机林间环境飞行参数设定方法。首先使用三维激光雷达所采集的林间点云数据进行建图，然后通过建图轨迹与GNSS-RTK数据轨迹进行对比分析，评价点云数据的质量，最后根据其均方根误差对无人机的最佳飞行高度与速度参数进行设定。分析结果表明：飞行速度固定时，机载激光雷达飞行轨迹的均方根误差与飞行高度成正相关。飞行高度固定时，机载激光雷达飞行轨迹的均方根误差与飞行速度成正相关。在平均高度为6~7 m，长度为100 m的林间，无人机的最佳飞行高度为12 m，最佳飞行速度为2 m/s，均方根误差为1.262 m。该方法满足评价点云数据质量的需求，同时为无人机林间环境飞行参数的设定提供理论支撑。

Research on setting method of UAV flight parameters based on SLAM

In order to overcome the problems of unreasonable flight parameters and poor point cloud data quality caused by the complex flight environment of UAVs in forests as well as diversified operations and difficulty in evaluating the quality of point cloud data, a method of setting flight parameters for UAV forest environment based on simultaneous localization and mapping was proposed. Firstly, the method constructed the forest point cloud data collected using 3D LiDAR. Secondly, the quality of the point cloud data was evaluated by comparing and analyzing the mapping trajectory and the GNSS-RTK data trajectory. Finally, the optimal flight altitude and speed parameters of the UAV were set according to its root mean square error. The analysis results showed that when the flight speed was fixed, the root mean square error of the flight path of the airborne lidar was positively correlated with the flight height. When the flight altitude was fixed, the root mean square error of the airborne LiDAR flight trajectory was positively correlated with the flight speed. In the forest with an average height of 6-7 m and a length of 100 m, optimal flying height of the UAV was 12 m, optimal flying speed was 2 m/s, and root mean square error was 1.262 m. This method meets the needs of evaluating the quality of point cloud data, and provides theoretical support for the setting of UAV flight parameters in forest environment.