针对单目视觉估计曲面物体位姿时世界坐标不易获得的问题,将双目视觉与合作靶标相结合,提出一种高效的曲面物体位姿估计方法。通过双目相机生成不同位姿下的目标物体点云以便快速提取靶标角点的世界坐标,不同于常用的点云配准位姿估计,本文取对应点坐标差的均值表示平移向量;然后,求取靶标角点所在切面的法向量,组成目标在不同位姿坐标系下的矩阵,从而推导出旋转矩阵。所提方法不仅保证了位姿估计结果的准确性与稳定性,而且算法的运行效率显著提高。实验结果表明,本文方法的运行效率相比ICP算法提高了98.24%,比NDT算法提高了97.58%,具有实际应用价值。

This work addresses the challenge of obtaining world coordinates when estimating the pose of curved objects through monocular vision. An efficient method for estimating the pose of curved objects is proposed herein. The proposed method combines binocular vision with the cooperative target. A point cloud of the target object in various poses is generated using a binocular camera in order to rapidly extract the world coordinates of the corner points of the target. Unlike the traditional point-cloud registration pose-estimation methods, the mean value of the corresponding point coordinate difference is used to represent the translation vector in the proposed method. The normal vector of the tangent plane comprising the target corner points is used to form a matrix of the target coordinates in different poses; thus, the rotation matrix is derived. The proposed method not only ensures the accuracy and stability of the pose estimation results but also improves the efficiency of the algorithm significantly. The experimental results show that the efficiency of the proposed method is 98.24% and 97.58% higher than those of the ICP algorithm and NDT algorithm, respectively. The proposed method to estimate the pose of curved objects has various practical applications that are reviewed in this work.