摘要
针对药品自动拣选过程中出现的位姿估计难度大、效率低等问题,提出一种平面分割与关键点匹配相结合的位姿估计方法.首先使用点云层次聚类算法对平面区域进行分割,并利用改进的二次关键点匹配方法对各线程中的药盒进行识别与定位,便于多线程处理.然后采用基于最小二乘的点云平面法向量估计方法实现药盒的姿态重建.实验采集存在视点变化、旋转变换和尺度变化的600幅图像进行测试,实验结果表明药盒位姿估计速度可达11帧/s,定位偏差小于5 mm,姿态估计偏差在2°以内.因此,所提方法是高效的,可以准确地识别药盒的位姿.
Aiming at the difficulty and low efficiency of pose estimation in the process of automatic drug picking,a pose estimation method combining plane segmentation and key point matching is proposed.First,a point cloud hierarchical clustering algorithm is used to segment the plane area,and the improved secondary key point matching method is used to identify and locate the pill box in each thread,which is convenient for multi-thread processing.Then the point cloud plane normal vector estimation method based on least squares is used to realize the posture reconstruction of the pill box.600 images with viewpoint change,rotation transformation and scale change were collected for testing,the experimental results show that the pose estimation speed of the medicine box can reach 11 frames/s,the positioning deviation is less than 5 mm,and the pose estimation deviation is within 2°.So the method is efficient and can accurately identify the pose of the medicine box.
作者
杨旭升
王帅炀
张文安
仇翔
Yang Xusheng;Wang Shuaiyang;Zhang Wen’an;Qiu Xiang(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2022年第4期570-580,共11页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(62173305,61903335)。
关键词
目标检测
平面分割
关键点匹配
位姿估计
target detection
plane segmentation
key point matching
pose estimation
