Interactive Generalized Penetration Depth Computation for Rigid and Articulated Models Using Object Norm
- 주제(키워드) Algorithms , Experimentation , Theory , Verification , Animation , dynamics , penetration depth , collision detection , articulated models
- 지원기관 This research was supported in part by NRF in Korea.
- 설명문(URI) http://dl.acm.org/citation.cfm?doid=2577382.2517108
- 관리정보기술 faculty
- 등재 SCIE, SCOPUS
- 발행기관 Association for Computing Machinery (ACM)
- 제작일 2014-01-01
- 발행년도 2014
- 원문페이지 15 p.
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000087248
- 본문언어 영어
- 저작권 이화여자대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
We present a novel, real-time algorithm to accurately approximate the generalized penetration depth (PDg) between two overlapping rigid or articulated models. Given the high complexity of computing PDg, our algorithm approximates PDg based on iterative, constrained optimization on the contact space, defined by the overlapping objects. The main ingredient of our algorithm is a novel and general formulation of distance metric, the object norm, in a configuration space for articulated models, and a compact closed-form solution for it. Then, we perform constrained optimization, by linearizing the contact constraint, and minimizing the object norm under such a constraint. In practice, our algorithm can compute locally optimal PDg for rigid or articulated models consisting of tens of thousands of triangles in tens of milliseconds. We also suggest three applications using PDg computation: retraction-based motion planning, physically-based animation, and data-driven grasping.
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