Study on the quality of drug vial recognition and grasping and opening for pharmacy intravenous admixture robot based on nanophotonic sensing

小瓶 药店 计算机科学 质量(理念) 机器人 人工智能 计算机视觉 医学 医学物理学 化学 色谱法 物理 护理部 量子力学
作者
Guochun Li,Ye Jiandong,Zhao Huaibi,Hòng Xu,Haiyang Jin,Huang Xinwu,Д.А. Гулин
标识
DOI:10.1016/j.slast.2025.100244
摘要

With the continuous progress of medical technology, traditional medicine bottle identification and management methods have problems such as low efficiency and large errors, and innovative solutions are urgently needed. Due to its high sensitivity and rapid response characteristics, this study aims to develop a robot system for intravenous infusion based on nanophotonics sensing to realize accurate identification, grasping and opening of medicine bottles in a dynamic environment, so as to improve the safety and efficiency of intravenous infusion. In this paper, an intelligent robot system with nanophotonics sensor is designed, which uses nanomaterials to produce high sensitivity sensor, so as to realize the information recognition of medicine bottle labels. The robot arm is set up to grasp and open the medicine bottle automatically through visual recognition system and feedback control algorithm. We conducted several rounds of experiments in a simulated environment to evaluate the recognition rate, grab success rate, and opening speed of the system. The experimental results show that the recognition system based on nano photonic sensor in bottle of accuracy and grab the success rate is higher, open time is greatly shortened, compared with traditional methods, the new system in recognition and operation were showed a significant advantage. The study demonstrates the potential of nanophotonics sensing technology in intravenous infusion robots. By optimizing the process of bottle recognition, grasping and opening, the system not only improves the safety and efficiency of medical operations, but is also expected to play a role in future medical automation. Future work will focus on further perfecting the system integration and optimization algorithm, so as to adapt to more complex clinical environment.

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