A Probabilistic Approach for On-line Positioning in Nano Manipulations
Nanomanipulation and nanoassembly using atom force microscopy (AFM) is a potential and promising technology for nanomanufacturing. Precise position of the tip of AFM is important to increase the accuracy and efficiency on fabricate complex nanostructures. However at the nanoscale, it is difficult to acquire the tip position expressed by the coordinate in real time due to PZT nonlinearity and thermal drift through the general measure. In this paper, a probabilistic approach incorporating a Kalman filter based localization algorithm is introduced into the on-line estimation of the tip position expressed by probability distribution known as probability density function. A probabilistic motion model of AFM tip is introduced that consists of a PZT dynamic model based on the Prandtl-Ishlinskii (PI) model, and motion error distribution obtained from calibration experiments. An observation model by using a local scanning algorithm is proposed and the change of uncertainty distribution on scanning landmarks, e.g. nano-particles, near the target position is analyzed. Some experiment results are included for showing the motion error distribution and a simulation result is presented to illustrate the validity of the proposed method.
Shuai Yuan Lianqing Liu Zhidong Wang Ning Xi Yuechao Wang Zaili Dong Zhiyu Wang
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, She State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, She State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, She State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, She
国际会议
The 8th World Congress on Intelligent Control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)
济南
英文
450-455
2010-07-07（万方平台首次上网日期，不代表论文的发表时间）