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Attitude Estimation Algorithm and Verification based on Binocular Vision of Micro Aerial Vehicles

机译:基于微空气车辆双筒望远镜的姿态估计算法和验证

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Aiming at the navigation of Micro Air Vehicles (MAVs) in the natural environment, an algorithm is studied to measure the attitude of MAVs based on binocular vision. Binocular images are taken by calibrated binocular camera. The image feature points are extracted by Harris algorithm, feature points are matched with Normalized Cross Correlation (NCC) algorithm, and obtained a set of matching points. The three dimensional coordinates of the feature points can be calculated in camera coordinate system. Then the attitude of MAVs is estimated by Singular Value Decomposition (SVD) method and Least Median Squares (LMedS) theorem. The experiment result shows that the attitude estimation error is small, which can meet the requirements of MAVs navigation.
机译:针对自然环境中微型空气车辆(MAV)的导航,研究了一种算法,以衡量基于双目视觉的MAVS的姿态。 双目图像是通过校准双目相机拍摄的。 图像特征点由Harris算法提取,特征点与归一化横相关(NCC)算法匹配,并获得了一组匹配点。 可以在相机坐标系中计算特征点的三维坐标。 然后通过奇异值分解(SVD)方法和最小中值正方形(LMEDS)定理估算MAVS的态度。 实验结果表明,姿态估计误差很小,这可以满足MAVS导航的要求。

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