文章摘要
沈永福,王希彬.基于边界的无人机主动SLAM算法[J].,2014,29(5):461-464
基于边界的无人机主动SLAM算法
UAV Active SLAM Algorithm Based on Boundary
  
DOI:10.7682/j.issn.1673-1522.2014.05.013
中文关键词: 主动同步定位与地图构建  边界  扩展卡尔曼滤波  人机
英文关键词: active simultaneous localization and mapping  boundary  extended kalman filtering (EKF)  unmanned aerial vehicle (UAV)
基金项目:
作者单位
沈永福 海军军训器材研究所,北京 102308 
王希彬 海军航空工程学院控制工程系,山东 烟台 264001 
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中文摘要:
      同步定位与地图构建技术是人机实现真正自主导航的关键。为克服被动同步定位与地图构建算法的缺陷,研究了基于边界的人机主动同步定位与地图构建算法。在人机的探测区域周围产生候选边界点,通过建立合理的目标函数,从候选边界点中选择目标点,控制人机朝该目标点方向运动,再运用扩展卡尔曼滤波算法更新人机的运动状态。通过建立的人机简化模型,对提出的算法和随机同步定位与地图构建算法进行对比研究,仿真结果表明该算法是有效可行的。
英文摘要:
      The technology of simultaneous localization and mapping (SLAM) is the key for an unmanned aerial vehicle (UAV) to realize truly autonomous navigation. To overcome the disadvantage of the passive SLAM, the active SLAM method based on boundary for UAV was studied. Firstly, the candidate boundary points were produced around the exploration area, and the destination point was selected from those points by building a proper objective function. Then the UAV moved towards this point and its movement state was updated by extended Kalman filtering (EKF) algorithm. Using a simplified model of UAV, comparative research was carried out between the proposed algorithm and random SLAM. The simulation results with Matlab showed that this algorithm was effective and feasible.
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