摘要
建立了多旋翼无人机动力学模型,并设计了应用于室内环境下的多旋翼无人机定位控制器。为提高定位精度,在室内设置了特定标签,从而为无人机提供视觉数据。通过扩展卡尔曼滤波器,将无人机传感器获得的惯性数据和高度数据与视觉数据进行融合,再通过飞行状态估计得到无人机实时的飞行位置信息。仿真结果表明,在融合视觉数据后,无人机飞行中的位置误差明显减小,无人机的定位精度获得明显的提高,说明定位控制器取得了良好的控制效果。
A dynamical model of multi-rotor UAVs was established, and a positioning controller of multi-rotor UAVs in an indoor environment was designed. In order to improve the accuracy of positioning, the specific tag was set to provide visual data for the UA V in interior space. Fusing the inertial data and the height data obtained from sensors of the UA V with visual data through the Extended Kalman Filter, and the UAV＇s position was obtained from the estimation of flight state in real time. Simulation results show that the error of the UAV＇s position reduces significantly after fusing the visual data, and the positioning accuracy of the UAV improved a lot, which shows that the controller works well.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2016年第10期2593-2599,共7页
Journal of System Simulation
基金
国家自然科学基金(41301428
4110143)
