Research on Pose Estimation Method of Medicine Box Based on Secondary Key Point Matching

Abstract

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.