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Cited by 182

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Staggered projections for frictional contact in multibody systems

Kaufman, Danny M., Sueda, Shinjiro, James, Doug L., Pai, Dinesh K.·2008·ACM Transactions on Graphics

Abstract

We present a new discrete velocity-level formulation of frictional contact dynamics that reduces to a pair of coupled projections and introduce a simple fixed-point property of this coupled system. This allows us to construct a novel algorithm for accurate frictional contact resolution based on a simple staggered sequence of projections. The algorithm accelerates performance using warm starts to leverage the potentially high temporal coherence between contact states and provides users with direct control over frictional accuracy. Applying this algorithm to rigid and deformable systems, we obtain robust and accurate simulations of frictional contact behavior not previously possible, at rates suitable for interactive haptic simulations, as well as large-scale animations. By construction, the proposed algorithm guarantees exact, velocity-level contact constraint enforcement and obtains long-term stable and robust integration. Examples are given to illustrate the performance, plausibility and accuracy of the obtained solutions.

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Metadata

Authors
Kaufman, D. M., Sueda, S., James, D. L., & Pai, D. K.
Venue
ACM Transactions on Graphics
Published
2008-12
Volume
27
Issue
5
Pages
1-11
ISSN
  • 0730-0301 (ISSN-L)
  • 1557-7368
OpenAlex
W1985640101
Cited by
182
References
1
FWCI
40.72
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Staggered projections for frictional contact in multibody systems. https://app.cochat.ai/papers/10.1145/1409060.1409117
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Kaufman, D. M., Sueda, S., James, D. L., & Pai, D. K. (2008). Staggered projections for frictional contact in multibody systems. ACM Transactions on Graphics. https://doi.org/10.1145/1409060.1409117

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.