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New Geometric Data Structures for Collision Detection and Haptics pp 49–89Cite as

Kinetic Data Structures for Collision Detection

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Part of the book series: Springer Series on Touch and Haptic Systems ((SSTHS))

Abstract

Deformable objects cause special problems to collision detection algorithms; first, pre-computed data structures like bounding volume hierarchies that are widely used for rigid objects become invalid if the geometry changes. Second, it is possible that parts of one object intersect other parts of the same object, the so-called self-collisions. In this chapter, we present several new algorithms that detect collisions between deformable objects more efficiently than previous approaches. For instance, we prove that our new kinetic AABB-Tree is optimal in the number of updates that is required to restore a bounding volume hierarchy after deformations. Moreover, our kinetic Separation-List can perform both, continuous collision and self-collision queries at interactive rates. Our new methods gain their efficiency from an event-based approach that relies on the framework of kinetic data structures.

Parts of this work has been previously published in [21] and [23].

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Authors and Affiliations

  1. Department of Computer Science, University of Bremen, Bremen, Germany

    René Weller

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  1. René Weller
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Weller, R. (2013). Kinetic Data Structures for Collision Detection. In: New Geometric Data Structures for Collision Detection and Haptics. Springer Series on Touch and Haptic Systems. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01020-5_3

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  • DOI: https://doi.org/10.1007/978-3-319-01020-5_3

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-01019-9

  • Online ISBN: 978-3-319-01020-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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