Vision-Based 40-nm-Accuracy Liquid Level Detection Compliant With Micromanipulation

被引:3
|
作者
Liang, Fei [1 ]
Zhao, Peng [1 ]
Feng, Yongxiang [1 ]
Wang, Wenhui [1 ]
机构
[1] Dept Precis Instrument, State Key Lab Precis Measurement Technol & Instru, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Liquids; Vibrations; Magnetic liquids; Optical surface waves; Surface waves; Surface morphology; End effectors; Computer vision; droplet-based assay; liquid level detection (LLD); micromanipulation; SENSOR; SYSTEM; WAVES;
D O I
10.1109/TIE.2021.3108700
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recent efforts in single-cell research call for precise liquid level detection (LLD) for end-effectors to manipulate small volume of liquid samples such as nano- to pico-liter droplets. Existing LLD methods, however, are yet satisfactory for such delicate micromanipulation tasks. This article presents a vision-based contact type LLD method, which adopts the hardware settings normally used in typical micromanipulation scenarios. The detection principle is based on the generation of patterned ripples when the end-effector (e.g., glass micropipette), that is being vibrated, moves to get contact with the liquid surface. Through the microscopic imaging system in micromanipulation, the image frames of patterned ripples such as concentric circles are recorded, from which the wavelength is extracted to determine the contact moment. The vision-based LLD method was cross-validated by the electrical impedance-based method. Experiments revealed that the best detection accuracy was 40 nm, only limited by the micromanipulator's positioning resolution. Moreover, the method was robust to various micromanipulation settings, such as illumination intensity, microscopy magnification, exposure time, and focal plane. As a demonstration, this method was successful in detecting the surface of droplets with a volume as low as 450 pL for different liquids. Given its generality, this method is expected to suit many scenarios involving liquid handling tasks in micromanipulation and industry.
引用
收藏
页码:8535 / 8544
页数:10
相关论文
共 50 条
  • [41] Vision-based Navigation and Obstacle Detection for UAV
    Li Jian
    Li Xiao-min
    2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC), 2011, : 1771 - 1774
  • [42] An insect vision-based motion detection chip
    Moini, A
    Bouzerdoum, A
    Eshraghian, K
    Yakovleff, A
    Nguyen, XT
    Blanksby, A
    Beare, R
    Abbott, D
    Bogner, RE
    IEEE JOURNAL OF SOLID-STATE CIRCUITS, 1997, 32 (02) : 279 - 284
  • [43] Vision-based pedestrian detection: The PROTECTOR system
    Gavrila, DM
    Giebel, J
    Munder, S
    2004 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 2004, : 13 - 18
  • [44] An Appearance-Motion Network for Vision-Based Crash Detection: Improving the Accuracy in Congested Traffic
    Zhou, Wei
    Wen, Longhui
    Zhan, Yunfei
    Wang, Chen
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (12) : 13742 - 13755
  • [45] Enhancing the accuracy of area extraction in machine vision-based pig weighing through edge detection
    Wang, Yongsheng
    Yang, Wade
    Walker, Lloyd T.
    Rababah, Taha M.
    International Journal of Agricultural and Biological Engineering, 2008, 1 (01) : 37 - 42
  • [46] Vision-based Target Detection in Road Environments
    Alvarez, S.
    Sotelo, M. A.
    Ocana, M.
    Fernandez, D.
    Parra, I.
    PROCEEDINGS OF THE 1ST WSEAS INTERNATIONAL CONFERENCE ON VISUALIZATION, IMAGING AND SIMULATION (VIS'08): RECENT ADVANCES IN VISUALIZATION, IMAGING AND SIMULATION, 2008, : 29 - 34
  • [47] A vision-based road edge detection algorithm
    Wang, RB
    Xu, YC
    Libin
    Zhao, YF
    IV'2002: IEEE INTELLIGENT VEHICLE SYMPOSIUM, PROCEEDINGS, 2002, : 141 - 147
  • [48] Vision-based Autonomous Detection of Lane and Pedestrians
    Kim, Dong-Uk
    Park, Sung-Ho
    Ban, Jong-Hee
    Lee, Taek-Min
    Do, Yongtae
    2016 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP), 2016, : 680 - 683
  • [49] Salience detection for vision-based robot navigation
    Celaya, E
    PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS 2003, VOL 1-3, 2003, : 345 - 350
  • [50] Reduction of Vision-Based Models for Fall Detection
    Garmendia-Orbegozo, Asier
    Anton, Miguel Angel
    Nunez-Gonzalez, Jose David
    SENSORS, 2024, 24 (22)