药品脱垛机器人系统

Patchara Opaspilai, S. Vongbunyong, Arbtip Dheeravongkit
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引用次数: 3

摘要

药品管理是医院工作中最复杂、最耗费人力的问题之一。并发症可导致许多严重的问题,特别是影响患者治疗过程的用药错误。管理涉及从外部供应商获取产品到给患者配药的各种物流活动。为了提高准确性和性能,已经进行了许多尝试,以实现这些过程的机器人和自动化。在本研究中,一个机器人系统被用于药品调剂前阶段的产品管理。自动分配器的杂志需要重新填充产品,例如药盒。一般来说,从供应商那里运输药品都是用包装箱的形式,里面有很多盒子。在这种情况下,SCARA机器人使用真空抓取器将包装箱内的盒子脱垛并重新排列到杂志中,以便进一步分配。该机器人配备了视觉系统,使该系统能够处理箱体包装在外观、尺寸和放置模式方面的变化。利用卷积神经网络(CNN)对盒子进行定位和分类,系统能够正确处理盒子。
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Robotic System for Depalletization of Pharmaceutical Products
Management of pharmaceutical products is one of the most complicated and labor-intensive issues in hospitals. The complication can lead to a number of serious problems, especially medication errors that affect the treatment process of patient. The management is involved various logistics activities from obtaining products from external suppliers to dispensing to patients. A number of attempts have been made to implement robotics and automation to these processes in order to improve accuracy and performance. In this research, a robot system used to manage the product at the stage before medicine dispensing. Automatic dispensers’ magazines need to be refilled with the products, e.g. medicine boxes. In general, the transportation of medicine from suppliers are in the form of packing case with a lot of boxes inside. In this case, SCARA robot with a vacuum gripper is used to depalletize boxes contained in the packing cases and rearrange them into magazines for further dispensing. The robot is equipped with vision system, so that the system is capable of handling variations of box packaging in term of appearance, size, and placement pattern. Convolutional Neural Network (CNN) has been applied to locate and classify the boxes and the system can treat them properly.
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