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Open AccessArticle

Visual Servoing-Based Nanorobotic System for Automated Electrical Characterization of Nanotubes inside SEM

by Huiyang Ding 1,†, Chaoyang Shi 2,†, Li Ma 1,*,‡, Zhan Yang 3,4,*,‡, Mingyu Wang 3, Yaqiong Wang 3, Tao Chen 3,4, Lining Sun 3,4 and Fukuda Toshio 5
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
Provincial Jiangsu Key Laboratory for Advanced Robotics, Soochow University, Suzhou 215123, China; [email protected] (M.W.)
Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou 215123, China
Intelligent Robotics Institute, School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081, China
Authors to whom correspondence should be addressed.
H. Ding and C. Shi contribute equally to this work and are co-first authors.
Denotes equal contribution and joint first authorship.
Sensors 2018, 18(4), 1137;
Received: 1 January 2018 / Revised: 25 March 2018 / Accepted: 26 March 2018 / Published: 8 April 2018
(This article belongs to the Section Physical Sensors)
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. View Full-Text
Keywords: automated nanomanipulation; visual servoing; carbon nanotubes (CNTs) automated nanomanipulation; visual servoing; carbon nanotubes (CNTs)
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Ding, H.; Shi, C.; Ma, L.; Yang, Z.; Wang, M.; Wang, Y.; Chen, T.; Sun, L.; Toshio, F. Visual Servoing-Based Nanorobotic System for Automated Electrical Characterization of Nanotubes inside SEM. Sensors 2018, 18, 1137.

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