引用本文:孔天恒,方舟,李平.基于雷达–扫描器/惯性导航系统的微小型无人机室内组合导航[J].控制理论与应用,2014,31(5):607~613.[点击复制]
KONG Tian-heng,FANG Zhou,LI Ping.Indoor integrated navigation of micro aerial vehicle based on radar-scanner and inertial navigation system[J].Control Theory and Technology,2014,31(5):607~613.[点击复制]
基于雷达–扫描器/惯性导航系统的微小型无人机室内组合导航
Indoor integrated navigation of micro aerial vehicle based on radar-scanner and inertial navigation system
摘要点击 3050  全文点击 2727  投稿时间:2013-07-10  修订日期:2014-02-19
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DOI编号  10.7641/CTA.2014.30711
  2014,31(5):607-613
中文关键词  微小型无人机  同步定位与构图  特征提取和匹配  扫描匹配  室内导航  卡尔曼滤波
英文关键词  micro aerial vehicle  simultaneous localization and mapping  feature extraction and matching  scan match- ing  indoor navigation  Kalman filter
基金项目  国家自然科学基金资助项目(61004066); 浙江省科技计划资助项目(2011C23106); 中央高校基本科研业务费资助项目(2011FZA4031).
作者单位E-mail
孔天恒 浙江大学 控制科学与工程学系 kongtianheng@gmail.com 
方舟* 浙江大学 控制科学与工程学系 zfang@zju.edu.cn 
李平 浙江大学 控制科学与工程学系
浙江大学 航空航天学院 
 
中文摘要
      本文提出一种基于雷达–扫描器/惯性导航系统(radar-scanner/INS)的微小型无人机室内导航方法. 为提高 算法的实时性, 采用基于扩展卡尔曼滤波(EKF)的D&C同步定位与构图技术(SLAM)实现定位和构图; 在更新状态 值的扫描匹配过程中提出启发性逻辑来筛选激光雷达数据, 以提高算法对无人机因姿态和高度变化而引起的轮廓 地图波动的抗干扰性; 在特征匹配的过程中选取合理的地图轮廓特征, 并利用扫描匹配的结果和特征匹配的传递性 提出了精度较高的引导配对, 以提高特征配对在三维环境下的准确性; 最后, 将D&C SLAM与惯性导航系统进行基 于EKF的组合滤波, 给出无人机的全状态估计. 通过与GPS/INS组合导航对比以及室内飞行验证, 本文提出的方法 能够满足无人机飞行控制对导航实时性和精度的要求.
英文摘要
      This paper presents an indoor integrated navigation method for micro aerial vehicles based on radar-scanner and inertial navigation system (INS). We employ the D&C simultaneous localization and mapping (SLAM) technique, which is actually an EKF-based SLAM algorithm, to meet the real-time requirements of the micro aerial vehicle (MAV) navigation. For the scan matching in state-update procedure, a heuristic logic is proposed to screen the radar data to deal with the strong perturbations on the map profile caused by the variations in attitude and height during the motion of MAV. We extract reasonable features from the map profile and use them in feature matching procedures. To improve the matching accuracy, we determine the guiding matching in pair-wise based on the result of scan matching and the transfer of feature matching. Finally, an integrated D