视觉约束下无人机位姿参数的后验估计

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朱枫, 刘昶, 吴清潇, 周静, 夏仁波. 视觉约束下无人机位姿参数的后验估计[J]. 机器人, 2012, 34(4): 424-431,439.. ZHU Feng, LIU Chang, WU Qingxiao, ZHOU Jing, XIA Renbo. UAV Pose Posterior Estimation with Vision Constraint. ROBOT, 2012, 34(4): 424-431,439..

摘要

针对无人机相对机场跑道的位姿估计问题，提出一种利用机场跑道图像和机载位姿测量传感器进行参数后验估计的方法．首先利用高度表、全球定位系统、惯性导航系统等机载传感器测量无人机的位姿参数．假设各参数的测量误差的先验分布已知且彼此独立，将某时刻的一组测量值看作是对真实值的一次采样．与此同时利用机载已标定相机拍摄跑道的图像，并假设两条跑道边缘直线可从图像中准确提取．受两平行直线透视成像的约束，真实参数必然位于参数空间中某个约束曲面上，进而计算得到位姿参数的后验均值估计．仿真结果验证了该方法的有效性．

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关键词 ：计算机视觉, 无人机（UAV）, 后验估计, 线特征

Abstract：

To estimate UAV (unmanned aerial vehicle) pose relative to airfield runway, a posterior parameter estimation method using the runway image and onboard pose sensors is presented. Firstly, pose parameters of UAV are measured by onboard sensors such as altimeter, GPS (global positioning system) and INS (inertial navigation system). Supposing the prior probability distribution of each parameter's measurement error is given and all errors are independent, the measured values from sensors can be considered as a sample of real ones. At the same time of sampling, an image of the runway is acquired from onboard calibrated camera, and the two edge lines of the runway are assumed to be extracted exactly from the image. Subject to the constraint of the perspective view of two parallel lines, the real parameters must locate on a constraint surface in the parameter space, and thereby the posterior mean estimation of the parameters can be obtained. Simulation results show that the method is effective.

Key words： computer vision unmanned aerial vehicle (UAV) posterior estimation line feature

收稿日期: 2011-12-26 录用日期: 2012-06-05

TP391

基金资助:

国家自然科学基金（51005229）

通讯作者: 朱枫 E-mail: fzhu@sia.cn

作者简介: 朱枫（1962-），男，博士，研究员，博士生导师．研究领域：计算机视觉，智能系统等．
刘昶（1971-），男，博士生，副教授．研究领域：计算机视觉，嵌入式系统等．
吴清潇（1978-），男，博士，副研究员．研究领域：图像处理，计算机视觉等．

链接本文:

https://robot.sia.cn/CN/ 或 https://robot.sia.cn/CN/Y2012/V34/I4/424

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