A convex decomposition methodology for collision detection

Chowriappa, Ashirwad; Wirz, Raúl; Ashammagari, Aditya Reddy; Kesavadas, Thenkurussi

doi:10.1109/vr.2013.6549361

Cited by 2 publications

(1 citation statement)

References 5 publications

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“…However, convex bounding volumes are the main research objects for most collision detection methods [16]. The convex partitioning method is always used in the collision detection of concave volumes, which detects each object collision after dividing the objects into several pieces [17][18]. The disadvantage of the convex partitioning method is that the detail of edges is lost if the number of pieces is low; on the other hand, the computing time of collision detection grows as the number of pieces increases.…”

Section: Introductionmentioning

confidence: 99%

Application of the Concave Arc Surface Collision Detection Method to Virtual Assembly

Shi¹,

Tian²

2021

Preprint

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Exact location calculation between each part of a parallel groove clamp when connecting a power line with a jumper is addressed in this paper. The relative location between a concave clamp and convex power line cannot be measured directly in live-line manipulation. We propose a concave arc surface collision detection method embedded in motion simulation. The relative location between irregular concave parts in the manipulation process can be obtained. The method is found to be computationally less expensive than convex partitioning collision detection techniques. This research provides a foundation for further study on robot hand manipulation with irregular assembly.

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Section: Introductionmentioning

confidence: 99%

Application of the Concave Arc Surface Collision Detection Method to Virtual Assembly

Shi¹,

Tian²

2021

Preprint

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Measurement-Driven Synthesis of Female Digital Mannequin Using Convex Sub-Volumes

Velez-Sanin

Gutierrez

Correa³

et al. 2022

Applied Sciences

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In the context of computer-aided apparel-fitting simulation, the problem of generating (a) simulation-inexpensive and (b) tailor-measurement-driven digital mannequins is central. Three-dimensional scanning of human bodies produces high-fidelity datasets. However, this technique does not satisfy conditions (a) and (b) above. In addition, it requires extensive data cleaning and processing. Existing approaches to this problem broadly fall into these mainstreams: (i) biased scaling, interpolation, or morphing of template models; or (ii) bottom-up construction of anatomy (bone medial axis, kinematic joints, muscles, skin, and other layers). Both alternatives imply extensive scanning, application of heuristics, tuning, and storage, among other tasks. Both alternatives produce non-convex datasets that have to be processed further for cloth–body interaction simulation, as physics engines require some type of data convexity for realistic simulations. This manuscript presents a modeling methodology that partially overcomes these limitations by (1) coarsely approximating a template female body with sets of convex volumes (ellipsoids and cushions), (2) building a set of Reference Mannequins for a particular set of extreme and average tailor measurements, and (3) creating sets of functions that synthesize new individuals of digital mannequins as reunions of convex volumes that satisfy specified tailor measurements. These mannequins present a reasonable and realistic demeanor. At the same time, they are shown to be economical at the stage of simulation of garment fitting. Future work is encouraged to define kinematic chains for straightforward pose definition, modeling male bodies, and exploring the behavior of the synthesis functions with more parameters.

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A convex decomposition methodology for collision detection

Cited by 2 publications

References 5 publications

Application of the Concave Arc Surface Collision Detection Method to Virtual Assembly

Application of the Concave Arc Surface Collision Detection Method to Virtual Assembly

Measurement-Driven Synthesis of Female Digital Mannequin Using Convex Sub-Volumes

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