针对现有药房药剂师取药任务繁重、效率低下等问题,设计了基于机器视觉的取药机器人系统,提出了一种基于融合局部特征匹配和Mean Shift算法的药品识别算法,系统整体实现了药品的识别、定位及抓取任务。首先,安装于药架之间的抓药机器人接收上位机发送的药品信息,通过摄像头识别药品,使用AKAZE算法对货架上的药品进行匹配,获取药品坐标后,将匹配的药品抓取放至传送带上;位于取药处的分拣机器人得到上位机发送的药品信息后,通过改进的Mean Shift算法对传送带上的动态药品进行二次识别,将识别到的药品抓取放至取药处,完成整个系统的取药功能。实验证明,以二次分拣为保证,系统能够准确地识别药品,且药品定位信息比较准确,误差较小,可适用于药房药品的抓取。

Aiming to solve the problems of complex drug-grabbing tasks and low efficiency of existing pharmacists, a vision-based drug-grabbing robot system is designed, and a drug-identification algorithm based on the fusion of local feature matching and based on Mean Shift algorithm is proposed. The complete system realizes drug identification, positioning, and grabbing tasks. The drug-grabbing robot installed between the drug racks receives information of the medicine sent by the upper computer, identifies the medicine through its camera, matches the medicine on the transporter using the AKAZE algorithm, obtains the coordinates of the medicine, and grabs and places the matched medicine on the transporter. After the sorting robot located in the designated area for taking the medicine obtains information of the medicine sent by the upper computer, the dynamic medicine on the transporter is identified twice via the improved Mean Shift algorithm, and the identified medicine is grabbed and placed in the designated area for taking the medicine to complete the taking function of the whole system. Experiments show that the system can accurately identify the drugs with the guarantee of secondary sorting and can accurately locate drug information with a small error, which is suitable for drug grabbing in pharmacies.