CAJ | 학술논문

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。
동보정위여지도구건기술시무인궤실현진정자주도항적관건。위극복피동동보정위여지도구건산법적결함，연구료기우변계적무인궤주동동보정위여지도구건산법。재무인궤적탐측구역주위산생후선변계점，통과건립합리적목표함수，종후선변계점중선택목표점，공제무인궤조해목표점방향운동，재운용확전잡이만려파산법경신무인궤적운동상태。통과건립적무인궤간화모형，대제출적산법화수궤동보정위여지도구건산법진행대비연구，방진결과표명해산법시유효가행적。
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 meth-od 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 sim-plified model of UAV, comparative research was carried out between the proposed algorithm and random SLAM. The simu-lation results with Matlab showed that this algorithm was effective and feasible.