Laboratory of Robotics, Faculty of Electrical Engineering, University of Ljubljana, Tržaška Cesta 25, 1000 Ljubljana, Slovenia.
Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Zaloška 4, 1000 Ljubljana, Slovenia.
Sensors (Basel). 2022 Apr 8;22(8):2862. doi: 10.3390/s22082862.
This study focuses on the feasibility of collaborative robot implementation in a medical microbiology laboratory by demonstrating fine tasks using kinesthetic teaching. Fine tasks require sub-millimetre positioning accuracy. Bacterial colony picking and identification was used as a case study. Colonies were picked from Petri dishes and identified using matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry. We picked and identified 56 colonies (36 colonies of Gram-negative and 20 colonies of Gram-positive ). The overall identification error rate was around 11%, although it was significantly lower for Gram-positive bacteria (5%) than Gram-negative bacteria (13.9%). Based on the identification scores, it was concluded that the system works similarly well as a manual operator. It was determined that tasks were successfully demonstrated using kinesthetic teaching and generalized using dynamic movement primitives (DMP). Further improvement of the identification error rate is possible by choosing a different deposited sample treatment method (e.g., semi-extraction, wet deposition).
本研究通过使用动觉教学演示精细任务，关注协作机器人在医学微生物学实验室中的实施可行性。精细任务需要亚毫米级的定位精度。细菌集落的挑取和鉴定被用作案例研究。从培养皿中挑取集落，并使用基质辅助激光解吸/电离（MALDI）飞行时间（TOF）质谱进行鉴定。我们挑取并鉴定了 56 个集落（革兰氏阴性菌 36 个，革兰氏阳性菌 20 个）。总体鉴定错误率约为 11%，尽管革兰氏阳性菌（5%）明显低于革兰氏阴性菌（13.9%）。基于鉴定分数，可以得出结论，该系统的表现与手动操作相似。通过使用动觉教学成功演示了任务，并使用动态运动基元（DMP）进行了推广。通过选择不同的沉积样本处理方法（例如半提取、湿沉积），可以进一步降低鉴定错误率。
