Ding Huiyang, Shi Chaoyang, Ma Li, Yang Zhan, Wang Mingyu, Wang Yaqiong, Chen Tao, Sun Lining, Toshio Fukuda
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada.
Sensors (Basel). 2018 Apr 8;18(4):1137. doi: 10.3390/s18041137.
The maneuvering and electrical characterization of nanotubes inside a scanning electron microscope (SEM) has historically been time-consuming and laborious for operators. Before the development of automated nanomanipulation-enabled techniques for the performance of pick-and-place and characterization of nanoobjects, these functions were still incomplete and largely operated manually. In this paper, a dual-probe nanomanipulation system vision-based feedback was demonstrated to automatically perform 3D nanomanipulation tasks, to investigate the electrical characterization of nanotubes. The XY-position of Atomic Force Microscope (AFM) cantilevers and individual carbon nanotubes (CNTs) were precisely recognized via a series of image processing operations. A coarse-to-fine positioning strategy in the Z-direction was applied through the combination of the sharpness-based depth estimation method and the contact-detection method. The use of nanorobotic magnification-regulated speed aided in improving working efficiency and reliability. Additionally, we proposed automated alignment of manipulator axes by visual tracking the movement trajectory of the end effector. The experimental results indicate the system's capability for automated measurement electrical characterization of CNTs. Furthermore, the automated nanomanipulation system has the potential to be extended to other nanomanipulation tasks.
在扫描电子显微镜（SEM）内部对纳米管进行操控和电学特性表征，对于操作人员来说，一直以来都是耗时费力的。在能够实现纳米物体拾取和放置以及表征功能的自动化纳米操控技术出现之前，这些功能仍不完善，且大多靠人工操作。本文展示了一种基于视觉反馈的双探针纳米操控系统，该系统能自动执行3D纳米操控任务，以研究纳米管的电学特性。通过一系列图像处理操作，精确识别了原子力显微镜（AFM）悬臂和单个碳纳米管（CNT）的XY位置。通过基于清晰度的深度估计方法和接触检测方法相结合，在Z方向上应用了从粗到精的定位策略。使用纳米机器人放大倍率调节速度有助于提高工作效率和可靠性。此外，我们通过视觉跟踪末端执行器的运动轨迹，提出了机械手轴的自动对齐方法。实验结果表明该系统具备对碳纳米管进行自动化电学特性测量的能力。此外，该自动化纳米操控系统有潜力扩展到其他纳米操控任务。
