提出了一种基于多传感器的三维目标位姿测量方法,该方法利用多传感器技术,充分发挥深度相机和高分辨率电荷耦合器件(CCD)相机各自的优势,提高了测量的稳健性和效率。利用物体与其固定平面之间的关系,在点云中粗略定位出目标区域,通过预先标定信息将目标区域转换至灰度图像空间。在灰度图像中,利用线段检测器(LSD)算法外加特征约束,筛选出4条目标直线,利用透视4点(P4P)算法求解出目标的六维位姿。实验验证了该算法的有效性,其测量效率远优于经典模板匹配方法。

A method based on multi-sensor to measure the pose of a three-dimensional object is proposed. We employ multi-sensor technology to make the advantages of the depth camera and the high-resolution charge-couple device (CCD) camera, improving the robustness and efficiency of measurement. The target area is coarsely located in the point cloud based on the relationship between the object and its fixed board, and the region is converted to gray image space by the prior calibration information. In the gray image, four target straight lines are extracted by the Line Segment Detector (LSD) and feature constraints. The perspective 4 point (P4P) algorithm is utilized to calculate the six-dimensional pose of the object. The experiment verifies the validity of the algorithm and the measurement efficiency of the algorithm is much better than that of the classical template matching method.