Local Optimization for Robust Signed Distance Field Collision

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Standard

Local Optimization for Robust Signed Distance Field Collision. / Macklin, Miles; Erleben, Kenny; Müller, Matthias; Chentanez, Nuttapong ; Jeschke, Stefan; Corse, Zach .

I: Proceedings of the ACM on Computer Graphics and Interactive Techniques, Bind 3, Nr. 1, 8, 2020.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Macklin, M, Erleben, K, Müller, M, Chentanez, N, Jeschke, S & Corse, Z 2020, 'Local Optimization for Robust Signed Distance Field Collision', Proceedings of the ACM on Computer Graphics and Interactive Techniques, bind 3, nr. 1, 8. https://doi.org/10.1145/3384538

APA

Macklin, M., Erleben, K., Müller, M., Chentanez, N., Jeschke, S., & Corse, Z. (2020). Local Optimization for Robust Signed Distance Field Collision. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 3(1), [8]. https://doi.org/10.1145/3384538

Vancouver

Macklin M, Erleben K, Müller M, Chentanez N, Jeschke S, Corse Z. Local Optimization for Robust Signed Distance Field Collision. Proceedings of the ACM on Computer Graphics and Interactive Techniques. 2020;3(1). 8. https://doi.org/10.1145/3384538

Author

Macklin, Miles ; Erleben, Kenny ; Müller, Matthias ; Chentanez, Nuttapong ; Jeschke, Stefan ; Corse, Zach . / Local Optimization for Robust Signed Distance Field Collision. I: Proceedings of the ACM on Computer Graphics and Interactive Techniques. 2020 ; Bind 3, Nr. 1.

Bibtex

@article{c02e6d42270a44fc8bd0ccd18ca052aa,
title = "Local Optimization for Robust Signed Distance Field Collision",
abstract = "Signed distance fields (SDFs) are a popular shape representation for collision detection. This is due to their query efficiency, and the ability to provide robust inside/outside information. Although it is straightforward to test points for interpenetration with an SDF, it is not clear how to extend this to continuous surfaces, such as triangle meshes. In this paper, we propose a per-element local optimization to find the closest points between the SDF isosurface and mesh elements. This allows us to generate accurate contact points between sharp point-face pairs, and handle smoothly varying edge-edge contact. We compare three numerical methods for solving the local optimization problem: projected gradient descent, Frank-Wolfe, and golden-section search. Finally, we demonstrate the applicability of our method to a wide range of scenarios including collision of simulated cloth, rigid bodies, and deformable solids.",
author = "Miles Macklin and Kenny Erleben and Matthias M{\"u}ller and Nuttapong Chentanez and Stefan Jeschke and Zach Corse",
year = "2020",
doi = "10.1145/3384538",
language = "English",
volume = "3",
journal = "Proceedings of the ACM on Computer Graphics and Interactive Techniques",
number = "1",

}

RIS

TY - JOUR

T1 - Local Optimization for Robust Signed Distance Field Collision

AU - Macklin, Miles

AU - Erleben, Kenny

AU - Müller, Matthias

AU - Chentanez, Nuttapong

AU - Jeschke, Stefan

AU - Corse, Zach

PY - 2020

Y1 - 2020

N2 - Signed distance fields (SDFs) are a popular shape representation for collision detection. This is due to their query efficiency, and the ability to provide robust inside/outside information. Although it is straightforward to test points for interpenetration with an SDF, it is not clear how to extend this to continuous surfaces, such as triangle meshes. In this paper, we propose a per-element local optimization to find the closest points between the SDF isosurface and mesh elements. This allows us to generate accurate contact points between sharp point-face pairs, and handle smoothly varying edge-edge contact. We compare three numerical methods for solving the local optimization problem: projected gradient descent, Frank-Wolfe, and golden-section search. Finally, we demonstrate the applicability of our method to a wide range of scenarios including collision of simulated cloth, rigid bodies, and deformable solids.

AB - Signed distance fields (SDFs) are a popular shape representation for collision detection. This is due to their query efficiency, and the ability to provide robust inside/outside information. Although it is straightforward to test points for interpenetration with an SDF, it is not clear how to extend this to continuous surfaces, such as triangle meshes. In this paper, we propose a per-element local optimization to find the closest points between the SDF isosurface and mesh elements. This allows us to generate accurate contact points between sharp point-face pairs, and handle smoothly varying edge-edge contact. We compare three numerical methods for solving the local optimization problem: projected gradient descent, Frank-Wolfe, and golden-section search. Finally, we demonstrate the applicability of our method to a wide range of scenarios including collision of simulated cloth, rigid bodies, and deformable solids.

U2 - 10.1145/3384538

DO - 10.1145/3384538

M3 - Journal article

VL - 3

JO - Proceedings of the ACM on Computer Graphics and Interactive Techniques

JF - Proceedings of the ACM on Computer Graphics and Interactive Techniques

IS - 1

M1 - 8

ER -

ID: 240981634