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AFM Tip Position Controlin situfor Effective Nanomanipulation

机译:AFM尖端位置控制就地有效进行纳米操作

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摘要

The spatial uncertainties of atomic force microscope (AFM) tip position hinder the development of the AFM-based nanomanipulation. These uncertainties cannot be corrected at nanoscale using the traditional position sensor, which is used in the macro robot localization. As for that problem, we propose that the AFM tip is used as the sensor to detect the landmark in the sample surface via a local-scan-based motion. The landmark positions are used to estimate the tip position in the task frame. The local-scan-based observation model is built on the foundation of the tip motion model. These model parameters are calibrated using statistical experiments. Simulation and experimental results show that the proposed method can improve the accuracy of the tip position. Then, the influence of the tip position accuracy is analyzed by using nanomanipulation results of the experiments. Furthermore, three important factors in AFM tip based nanomanipulation are discussed. The landmark domain as the first factor is analyzed for assurance of the tip accuracy before nanomanipulation. The second one is studying the contact characteristics between the nanoparticle and the substrate by detecting nanomanipulation force. The last one is taking the tip shape into account for effective manipulation through fine-tuning the tip offset. Finally, the experimental results illustrate the effectiveness of the proposed method for fabricating the nanostructures and devices.
机译:原子力显微镜(AFM)尖端位置的空间不确定性阻碍了基于AFM的纳米操作的发展。这些不确定性无法使用在宏机器人定位中使用的传统位置传感器进行纳米级校正。对于该问题,我们建议将AFM尖端用作传感器,以通过基于本地扫描的运动来检测样品表面中的界标。界标位置用于估计任务框中的笔尖位置。基于局部扫描的观察模型建立在尖端运动模型的基础上。这些模型参数使用统计实验进行校准。仿真和实验结果表明,该方法可以提高笔尖位置的精度。然后,通过使用实验的纳米操作结果来分析尖端位置精度的影响。此外,讨论了基于AFM尖端的纳米操作中的三个重要因素。分析地标域作为第一因素,以确保在纳米操作之前尖端的准确性。第二个是通过检测纳米操纵力来研究纳米粒子与基材之间的接触特性。最后一个是考虑到尖端形状,以通过微调尖端偏移来进行有效操作。最后,实验结果说明了所提出的用于制造纳米结构和器件的方法的有效性。

著录项

  • 来源
    《Mechatronics, IEEE/ASME Transactions on》 |2018年第6期|2825-2836|共12页
  • 作者单位

    State Key Laboratory of Robotics in Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;

    Department of Advanced Robotics, Chiba Institute of Technology, Chiba, Japan;

    Department of Industrial and Manufacturing Systems Engineering, Emerging Technologies Institute, Faculty of Engineering, University of Hong Kong, Hong Kong;

    State Key Laboratory of Robotics in Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;

    State Key Laboratory of Robotics in Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Uncertainty; Robot sensing systems; Task analysis; Random variables; Trajectory; Calibration; Kalman filters;

    机译:不确定度;机器人传感系统;任务分析;随机变量;轨迹;校准;卡尔曼滤波器;

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