• DocumentCode
    2556521
  • Title

    A computer vision based machine for automated packaging of photonics components

  • Author

    Ault, Stanley K. ; Strand, Oliver T. ; Lowry, Mark E.

  • Author_Institution
    Lawrence Livermore Nat. Lab., CA, USA
  • Volume
    2
  • fYear
    1996
  • fDate
    18-21 Nov. 1996
  • Firstpage
    238
  • Abstract
    Three low-cost machines were designed and built under an ARPA-funded project to perform sub-micron alignments and attachments of single-mode fibers to different OE devices. These Automated Fiber Pigtailing Machines (AFPMs) are compatible with a manufacturing environment and have a modular design for standardization of parts and machine vision for maximum flexibility. The vision system greatly reduces mechanical fixturing constraints by requiring the critical components to be positioned only within the 1 mm field of view of the camera. Object-recognition algorithms allow the AFPM to quickly determine the initial locations of the OE device and the fiber and to position the fiber with sufficient accuracy for fine alignment via optical throughput maximization.
  • Keywords
    computer vision; image processing equipment; object recognition; optical fibre couplers; optical fibre fabrication; packaging; position control; production engineering computing; automated fiber pigtailing machines; automated packaging; computer vision based machine; critical component positioning; fine alignment; manufacturing environment compatibility; mechanical fixturing constraints; modular design; object-recognition algorithms; optical throughput maximization; photonics components; single-mode fibers; submicron alignment; Cameras; Computer vision; Fixtures; Machine vision; Manufacturing automation; Optical devices; Optical fiber devices; Packaging machines; Standardization; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Lasers and Electro-Optics Society Annual Meeting, 1996. LEOS 96., IEEE
  • Conference_Location
    Boston, MA, USA
  • Print_ISBN
    0-7803-3160-5
  • Type

    conf

  • DOI
    10.1109/LEOS.1996.571641
  • Filename
    571641