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13. Front Matter.

Author

Zhang, Wendong, Chou, Xiujian, Shi, Tielin, Ma, Zongmin, Bao, Haifei, Chen, Jing, Chen, Liguo, Li, Dachao, and Xue, Chenyang

Published
2016
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16. Introduction.

Author

Zhang, Wendong, Chou, Xiujian, Shi, Tielin, Ma, Zongmin, Bao, Haifei, Chen, Jing, Chen, Liguo, Li, Dachao, and Xue, Chenyang

Published
2016
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20. A Sidewall Piezoresistive Force Sensor Used in a MEMS Gripper.

Author

Chen, Tao, Chen, Liguo, Sun, Lining, Wang, Jiachou, and Li, Xinxin

Abstract

This work reports the design and development of a MEMS based, piezoresistive sensor for micro-force measurement. Surface and bulk micromachining technology is employed to fabricate the force sensor from single crystal silicon wafer (i.e., no silicon on insulator wafer is used). Boron diffusion process combined with deep reactive ionic etching (DRIE) technique is used to form the side direction force sensors. The force sensor is integrated in a four arms structure MEMS gripper to experimentally verify the performance of the sensor. The resolution of the force sensor is in the micronewton range and, therefore, provides feedback of the forces that dominate the micromanipulation processes. Testing results show that the sensitivity of the piezoresistive sensors is better than 72V/N and the resolution is better than 3μN. Experimental show that it can successfully provide force sensing and play a main role in preventing damage of microparts in micromanipulation and microassembly tasks. [ABSTRACT FROM AUTHOR]

Published
2008
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21. Three-Dimensional Tracking at Micro-scale Using a Single Optical Microscope.

Author

Chen, Liguo, Yang, Zhiliang, and Sun, Lining

Abstract

3D tracking is of fundamental importance to the development of practical visual applications to micromanipulation and microassembly. In this paper, a new 3D tracking method based on CAMSHIFT and Depth-from-Defocus is developed for micromanipulation and microassembly task. CAMSHIFT algorithm is used to find the size and location of moving object even the micro-objects is highly blurred. And Depth-from-defocus method is used to recover the depth information of the object from a measure of the level of defocus. The experimental results of blurring tracking and depth recovery of micro gear validate the feasibility of the proposed 3D tracking method. [ABSTRACT FROM AUTHOR]

Published
2008
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