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Lodos-v2: An Efficient Primal Formulation of the Exact Frictional Contact Problem

1 reports1 reporting sourcesUpdated 21 hours ago

Overview

Event synthesis

This paper introduces Lodos-v2, a GPU-based simulation framework designed for high-throughput rigid-body dynamics with contact. It resolves limitations in its predecessor, Lodos-v1, by solving the exact frictional contact problem through sequential convex relaxations in primal form and extending the contact-group reparameterization scheme to integrate with full simulator constraints like joint limits. Experiments show improved throughput over established frameworks, with source code available on GitHub.

Generated from attributed reports · Updated 20 hours ago

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Environment: simulation
Supporting report

“arXiv:2611.08868v1 Announce Type: new Abstract: Lodos-v2 is a GPU-based simulation framework for massively parallel rigid-body dynamics with contact. It is specifically designed to achieve high throughput in scenes involving collisions among large numbers of detailed meshes. Its predecessor, Lodos-v1, had two main limitations. First, it solved the standard convex relaxation of cone-complementarity-based contact dynam”

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Supporting report

“cs, enabling its integration with the other constraints of a full-fledged simulator. Experiments demonstrate that these contributions result in throughput improvements over established rigid-body simulation frameworks. The source code is available at https://github.com/martius-lab/lodos.”

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11/9
  1. arXiv Robotics — research abstractsSignal
    Lodos-v2: An Efficient Primal Formulation of the Exact Frictional Contact Problem

    This paper introduces Lodos-v2, a GPU-based simulation framework designed for high-throughput rigid-body dynamics with contact. It resolves limitations in its predecessor, Lodos-v1, by solving the exact frictional contact problem through sequential convex relaxations in primal form and extending the contact-group reparameterization scheme to integrate with full simulator constraints like joint limits. Experiments show improved throughput over established frameworks, with source code available on GitHub.

Event coverage history

Current attention 6·Peak within the comparable range 10(2026-11-09 06:00 UTC)·Change within the comparable range over 24 hours –

02.557.5102026-11-0906:002026-11-0912:002026-11-0919:002026-11-1001:00

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