基于边界的无人机主动SLAM算法
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(1. 海军军训器材研究所,北京 102308;2. 海军航空工程学院控制工程系,山东 烟台 264001)

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V24

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UAV Active SLAM Algorithm Based on Boundary
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(1. Naval Training Equipment Institute, Beijing 102308, China;2. Department of Control Engineering, NAAU, Yantai Shandong 264001, China)

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    摘要:

    同步定位与地图构建技术是无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,研究了基于边界的无人机主动同步定位与地图构建算法。在无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,控制无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无人机的运动状态。通过建立的无人机简化模型,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。

    Abstract:

    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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沈永福,王希彬.基于边界的无人机主动SLAM算法[J].海军航空大学学报,2014,29(5):461-464
SHEN Yong-fu, WANG Xi-bin. UAV Active SLAM Algorithm Based on Boundary[J]. JOURNAL OF NAVAL AVIATION UNIVERSITY,2014,29(5):461-464

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  • 在线发布日期: 2015-01-16
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