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Efficient collision detection within deforming spherical sliding contact.

Anderson Maciel1, Ronan Boulic, Daniel Thalmann

  • 1Rensselaer Polytechnic Institute, Troy, NY 12180, USA. maciea@rpi.edu

IEEE Transactions on Visualization and Computer Graphics
|March 16, 2007
PubMed
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This study introduces a novel collision detection method for dynamic soft-tissue contact in medical simulations. The approach efficiently calculates distances between deforming meshes, reducing computational cost for virtual human models.

Area of Science:

  • Computational geometry
  • Biomechanics
  • Medical simulation

Background:

  • Collision detection in simulations with deformable objects is computationally intensive.
  • Increasing complexity of virtual human models, especially in medical applications, necessitates efficient handling of permanent contact.
  • Soft structures in dynamic contact, typical of 3D biological elements, pose a significant challenge.

Purpose of the Study:

  • To propose a novel, computationally efficient collision detection approach for soft structures in dynamic contact.
  • To address the high computing cost associated with evolving permanent contact of deformable objects.
  • To facilitate advanced medical applications using complex virtual human models.

Main Methods:

  • A two-stage approach involving preprocessing and collision detection.

Related Experiment Videos

  • Preprocessing: Selection of a reference mesh and spherical sampling.
  • Collision detection: Exploiting a precomputed table for constant-time signed distance calculation for each vertex of the mobile mesh.

    • Main Results:

    • The method achieves constant-time signed distance calculation for vertices of the mobile mesh.
    • It effectively handles large relative displacements, reorientations, and deformations of the mobile mesh.
    • Demonstrated efficacy on a biomechanical model of the human hip joint compared to other techniques.

    Conclusions:

    • The proposed method offers an efficient solution for collision detection in dynamic soft-tissue contact scenarios.
    • It is well-suited for applications involving deforming anatomical systems with layered configurations and bounded tangential deformation.
    • This approach has the potential to enhance the realism and performance of medical simulations.