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Integration of vision based image processing for multi-axis CNC machine tool safe and efficient trajectory generation and collision avoidance

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Demand of high speed production not only increases the complexity of today's CNC process, but also increases the risks and possibility of collision because of the difference between real (machining) and virtual scenes (CAD/CAM process). Idea here is to make this process more intelligent by processing image taken from the real or virtual machine scenes. Identify objects (already known in the CAD database), obtain safe and efficient trajectories that will modify the previous known trajectories from the CAM systems and will be used finally in real machining environments. This work more focuses to improve trajectory generation, collision avoidance and communication in CAD/CAM systems by image processing technique. Safe and Efficient Trajectory (SET) algorithm for point trajectory is discussed along with its extended version for object trajectory known as Rectangular Enveloped object Safe and Efficient Trajectory (RESET) algorithm that will perfectly generate safe un-functional trajectories [3] for multi-axis machine tool envelop. Meanwhile scene objects are detected and identified by image processing tool while trajectory and setup is optimized and improved accordingly in order to avoid collision. This generated trajectory can be used for setup correction before and after production or for "real times/online" production. Finally work has been validated through real and virtual machine scene images.
Rocznik
Strony
53--65
Opis fizyczny
Bibliogr. 14 poz., tab., rys.
Twórcy
Bibliografia
  • [1] AA ATA and TR MYO., 2006, Collision-free trajectory planning for manipulators using generalized pattern search, International Journal of Simulation and Modelling, 5/4, 145–154.
  • [2] O. DE VEL and S. AEBERHARD., 2000, Object recognition using random image-lines. Image and Vision Computing, 18/3, 193–198.
  • [3] J-Y. HASCOET, F. BENNIS and F. GUERIN., 1993, Optimization of tool trajectory for five axis control machining, Int. Conf. Iasted Robotics and Manufacturing, 120–122.
  • [4] J.Y. HASCOET, M. RAUCH and S.H. SUH., 2007, Relevance of step-nc standard for high level toolpaths generation. Int. Conference on High Speed Milling.
  • [5] LEI HE, CHIA Y. HAN, BRYAN EVERDING and WILLIAM G., 2004, Wee. Graph matching for object recognition and recovery, Pattern Recognition, 37/7, 1557–1560.
  • [6] S. HO, S. SARMA and Y. ADACHI., 2001, Real-time interference analysis between a tool and an environment. Computer-Aided Design, 33/13, 935–947.
  • [7] OLEG ILUSHIN, GERSHON ELBER, DAN HALPERIN, RON WEIN and MYUNG-SOO KIM., 2005, Precise global collision detection in multi-axis nc-machining. Computer-Aided Design, Special Issue: Product Design, Integration and Manufacturing, 37/9, 909–920.
  • [8] SEUNGJIN LEE, KWANHO KIM, JOO-YOUNG KIM, MINSU KIM and HOI-JUN YOO., 2010, Familiarity based unified visual attention model for fast and robust object recognition. Pattern Recognition, 43/3, 1116– 1128.
  • [9] YANG-LYUL LEE and RAE-HONG PARK., 2002, A surface-based approach to 3-d object recognition using a mean field annealing neural network. Pattern Recognition, 35/2, 299–316.
  • [10] KOICHI MORISHIGE, KIWAMU KASE and YOSHIMI TAKEUCHI., 1997, Collision-free tool path generation using 2-dimensional c-space for 5-axis control machining. The International Journal of Advanced Manufacturing Technology, 13, 393–400.
  • [11] PRALAY PAL and ANJANI KUMAR., 2002, A hybrid approach for identification of 3d features from cad database for manufacturing support. International Journal of Machine Tools and Manufacture, 42/2, 221–228.
  • [12] T.D. TANG, ERIK L.J. BOHEZ and PISUT KOOMSAP., 2007, The sweep plane algorithm for global collision detection with workpiece geometry update for five-axis nc machining. Computer-Aided Design, 39/11, 1012– 1024.
  • [13] XIAODONG TIAN, XI ZHANG, KAZUO YAMAZAKI and ADAM HANSEL., 2010, A study on three dimensional vision system for machining setup verification. Robotics and Computer- Integrated Manufacturing, 26/1, 46–55.
  • [14] QING-HUI WANG, JING-RONG LI and RU-RONG ZHOU., 2006, Graphics-assisted approach to rapid collision detection for multi-axis machining, The International Journal of Advanced Manufacturing Technology, 30, 853–863.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-952858d9-3e90-4673-a124-b21f6d8beb61
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