• DocumentCode
    2330047
  • Title

    Collision detection with improved algorithm based on k-dop

  • Author

    Gao Mingxiang ; Dingfang, Chen

  • Author_Institution
    Res. Inst. of Intell. Manuf. & Control, Wuhan Univ. of Technol., Wuhan
  • fYear
    2009
  • fDate
    25-27 May 2009
  • Firstpage
    102
  • Lastpage
    105
  • Abstract
    In this thesis, a new k-dop-based algorithm is presented to detect collisions between two flying objects in virtual environment (VE). The core of our algorithm is that, we build environment bounding volume tree (BVT) for each leaf nodes of flying BVT. When checking for overlaps between two leaf nodes NA and NB of two flying BVTs, we perform the overlap test between NB and the environment BVT of NA with the popular k-dop-based but updated algorithm at first. With the test, a set T of triangles intersecting with the bounding volume of NA is setup quickly, these triangles are all from NB. Then check the overlap pairs between triangles in NA and triangles in set T with triangle-triangle overlap test. Comparing with the method directly using triangle-triangle overlap test for two flying leaf nodes, our algorithm can fast exclude the non-overlap triangles. With the new algorithm, fast and exact collision detection in VE consisting of multi flying objects has also been implemented.
  • Keywords
    computational geometry; trees (mathematics); virtual reality; collision detection; environment bounding volume tree; flying objects; improved algorithm; k-dop-based algorithm; leaf nodes; nonoverlap triangles; triangle-triangle overlap test; virtual environment; Algorithm design and analysis; Intelligent control; Manufacturing; Niobium; Object detection; Performance evaluation; Slabs; Solid modeling; Testing; Virtual environment; collision detection; environment object; flying object; k-dop;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-2799-4
  • Electronic_ISBN
    978-1-4244-2800-7
  • Type

    conf

  • DOI
    10.1109/ICIEA.2009.5138178
  • Filename
    5138178