弱纹理条件下无人机姿态参数估计
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Attitude Parameter Estimation of UAV under Weak Texture Condition
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    摘要:

    基于视觉定位的无人机在弱纹理环境下,位置容易产生漂移,针对该问题,提出一种基于改进Snake算法与ORB (oriented FAST and rotated BRIEF)特征光流相结合的方法,对无人机运行参数进行估计,从而改善漂移.首先,采用高斯滤波对采集视频帧进行去噪处理;然后,计算视频帧灰度共生矩阵,判断是否均处于弱纹理区域,若均为弱纹理部分,采用ORB光流算法对参数进行估计;若存在非弱纹理区域,使用改进Snake模型,计算该区域重心,估计移动估计.使用单应性矩阵,分解得到旋转分量.通过在室内的实验,可以验证本方法在弱纹理区域及非弱纹理区域,参数估计正确率均高于95%,平均处理时间达到25 ms.

    Abstract:

    Unmanned aerial vehicle (UAV) based on visual positioning is prone to drift in a weak texture environment. To solve the problem, this study proposes a method integrating the improved Snake algorithm and ORB (oriented FAST and rotated BRIEF) feature optical flow to estimate the operating parameters of UAV. Firstly, Gaussian filtering is used to denoise the collected video frames. Then, the gray level co-occurrence matrix of video frames is calculated, and whether they are all in the weak texture area is judged. If they are all weak texture parts, ORB optical flow algorithm is used to estimate the parameters. If there is a non-weak texture area, the center of gravity of the area is calculated by the improved Snake model, by which the drift is estimated. With the homography matrix, the rotation component is obtained by decomposition. Laboratory experiments verify that the accuracy of parameter estimation is higher than 95% and the average processing time is as short as 0.025 s in both weak and non-weak texture areas.

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张娣,杨硕.弱纹理条件下无人机姿态参数估计.计算机系统应用,2022,31(1):168-174

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历史
  • 收稿日期:2021-03-13
  • 最后修改日期:2021-04-07
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  • 在线发布日期: 2021-12-17
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