系统仿真学报 ›› 2016, Vol. 28 ›› Issue (10): 2593-2599.

• 仿真系统与技术 • 上一篇    下一篇

基于数据融合的多旋翼无人机定位控制器设计

王庆贺, 万刚, 曹雪峰, 谢理想   

  1. 信息工程大学,郑州 450052
  • 收稿日期:2016-05-20 修回日期:2016-07-11 出版日期:2016-10-08 发布日期:2020-08-13
  • 作者简介:王庆贺(1991-),男,安徽利辛,硕士,研究方向为无人机智能控制与航迹规划;万刚(1972-),男,河北保定,教授,研究方向为虚拟地理环境构建和空间认知。
  • 基金资助:
    国家自然科学基金(41301428,4110143)

Design of Multi-Rotor UAVs’ Positioning Controller Based on Data Fusion

Wang Qinghe, Wan Gang, Cao Xuefeng, Xie Lixiang   

  1. Information Engineering University, Zhengzhou 450052, China
  • Received:2016-05-20 Revised:2016-07-11 Online:2016-10-08 Published:2020-08-13

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。

关键词: 动力学模型, 视觉数据, 扩展卡尔曼滤波, 数据融合, 定位控制器

Abstract: 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 UAV in interior space. Fusing the inertial data and the height data obtained from sensors of the UAV 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.

Key words: dynamical model, visual data, extended kalman filter, data fusion, positioning controller

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