Class #6: Collision Detection and Distance Computation



The figure on the left illustrates the coherence principle on which feature-tracking methods are based. The figures on the center illustrate the application of feature-tracking to detect self-collision in a humanoid robot. The image on the right depicts a “triangulated cat” and a subset of the sphere hierarchy used to approximate this model at successive levels for hierarchical collision detection.

  • Topics:
    - Feature-tracking approach
    - Application to detection of self-collision in a humanoid robot
    - Bounding Volume Hierarchy (BVH) approach
    - Static vs. dynamic collision checking
  • Required Readings:
    • Basic paper on feature-tracking approach:
      M. Lin and J. Canny. A Fast Algorithm for Incremental Distance Calculation. Proc. IEEE Int.
      Conf. on Robotics and Automation
      , pp. 1008-1014, 1991. [pdf]
    • Bounding Volume Hierarchy (with spheres):
      S. Quinlan. Efficient Distance Computation Between Non-Convex Objects. Proc. IEEE Int. Conf. on Robotics and Automation, 1994. [pdf]

  • Other Readings:
    • Grid method:
      D. Halperin and M.H. Overmars  Spheres, Molecules, and Hidden Surface Removal. Computational Geometry: Theory and Applications 11 (2), 1998, 83-102.  [pdf]

    • Self-collision detection in humanoid robot:
      J. Kuffner et al. Self-Collision and Prevention for Humanoid Robots. Proc. IEEE Int. Conf. on Robotics and Automation, 2002. [pdf]

    • Adaptive bisection in dynamic collision checking
      F. Schwarzer, M. Saha, J.C. Latombe. Adaptive Dynamic Collision Checking for Single and Multiple Articulated Robots in Complex Environments, manuscript, 2003. [pdf]
  • Slides