GPU-Based Collision Detection and Resolution for Elastic Polyhedral Meshes | TU Wien

Information

Publication Type: Master Thesis
Workgroup(s)/Project(s):
- Advanced Computational Design
Date: September 2026
Date (Start): January 2026
Date (End): September 2026
TU Wien Library: AC18093322
Second Supervisor: David Hahn
Diploma Examination: 28. September 2026
Open Access: yes
First Supervisor:
- David Hahn
- Michael Wimmer
Pages: 79
Keywords: Computer Graphics, GPU Computing, Physics-Based Simulation, Collision Detection, Collision Resolution, Image-Based Collision Detection, Polyhedral Meshes, Deformable Geometry, Virtual Element Method

Abstract

Collision handling for deformable objects is particularly challenging when their volumes are discretized into general polyhedral elements. Unlike standard tetrahedral meshes, these elements have irregular topology, may contain non-planar polygonal faces, and can become non-convex during simulation. This thesis presents a collision handling pipeline for elastic polyhedral meshes that runs entirely on the GPU and extends an existing Virtual Element Method simulation framework. Our pipeline traverses a Bounding Volume Hierarchy (BVH) to generate candidate pairs of intersecting element Axis-Aligned Bounding Boxes (AABBs). Topological neighborhood information and an active-element classification avoid tests that cannot produce relevant contact. For the remaining pairs, an image-based collision detection method, adapted from previous work, rasterizes a triangulated representation of the polyhedral surfaces using a custom CUDA compute rasterizer. A position-based correction approach is then used to reduce interpenetration between colliding elements and also computes resulting forces to be fed into the subsequent solver iteration. Our evaluation showes that the detection method is accurate, the detected pairwise overlap is generally reduced over time and active-element and neighborhood filtering avoid many unnecessary collision tests. Among the three collision-handling stages, the image-based narrow phase has the most dominant runtime and memory cost and is therefore the primary target for further optimization. Overall, the implementation provides a practical foundation for GPU-based collision handling on deformable polyhedral meshes and identifies several directions for future work.

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BibTeX

@mastersthesis{Fuericht-2026-GPUCDR,
  title =      "GPU-Based Collision Detection and Resolution for Elastic
               Polyhedral Meshes",
  author =     "Elias F\"{u}richt",
  year =       "2026",
  abstract =   "Collision handling for deformable objects is particularly
               challenging when their volumes are discretized into general
               polyhedral elements. Unlike standard tetrahedral meshes,
               these elements have irregular topology, may contain
               non-planar polygonal faces, and can become non-convex during
               simulation. This thesis presents a collision handling
               pipeline for elastic polyhedral meshes that runs entirely on
               the GPU and extends an existing Virtual Element Method
               simulation framework. Our pipeline traverses a Bounding
               Volume Hierarchy (BVH) to generate candidate pairs of
               intersecting element Axis-Aligned Bounding Boxes (AABBs).
               Topological neighborhood information and an active-element
               classification avoid tests that cannot produce relevant
               contact. For the remaining pairs, an image-based collision
               detection method, adapted from previous work, rasterizes a
               triangulated representation of the polyhedral surfaces using
               a custom CUDA compute rasterizer. A position-based
               correction approach is then used to reduce interpenetration
               between colliding elements and also computes resulting
               forces to be fed into the subsequent solver iteration. Our
               evaluation showes that the detection method is accurate, the
               detected pairwise overlap is generally reduced over time and
               active-element and neighborhood filtering avoid many
               unnecessary collision tests. Among the three
               collision-handling stages, the image-based narrow phase has
               the most dominant runtime and memory cost and is therefore
               the primary target for further optimization. Overall, the
               implementation provides a practical foundation for GPU-based
               collision handling on deformable polyhedral meshes and
               identifies several directions for future work.",
  month =      sep,
  pages =      "79",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Research Unit of Computer Graphics, Institute of Visual
               Computing and Human-Centered Technology, Faculty of
               Informatics, TU Wien",
  keywords =   "Computer Graphics, GPU Computing, Physics-Based Simulation,
               Collision Detection, Collision Resolution, Image-Based
               Collision Detection, Polyhedral Meshes, Deformable Geometry,
               Virtual Element Method",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2026/Fuericht-2026-GPUCDR/",
}