NDLI: Continuous collision detection for articulated models using Taylor models and temporal culling

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Continuous collision detection for articulated models using Taylor models and temporal culling

Content Provider	ACM Digital Library
Author	Redon, Stephane Lee, Minkyoung Zhang, Xinyu Kim, Young J.
Abstract	We present a fast continuous collision detection (CCD) algorithm for articulated models using Taylor models and temporal culling. Our algorithm is a generalization of conservative advancement (CA) from convex models [Mirtich 1996] to articulated models with non-convex links. Given the initial and final configurations of a moving articulated model, our algorithm creates a continuous motion with constant translational and rotational velocities for each link, and checks for interferences between the articulated model under continuous motion and other models in the environment and for self-collisions. If collisions occur, our algorithm reports the first time of contact (TOC) as well as collision witness features. We have implemented our CCD algorithm and applied it to several challenging scenarios including locomotion generation, articulated-body dynamics and character motion planning. Our algorithm can perform CCDs including self-collision detection for articulated models consisting of many links and tens of thousands of triangles in 1.22 ms on average running on a 3.6 GHz Pentium 4 PC. This is an improvement on the performance of prior algorithms of more than an order of magnitude.
File Format	PDF MP4
ISSN	07300301
DOI	10.1145/1275808.1276396
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-08-05
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Articulated models Continuous collision detection Conservative advancement Convex decomposition Dynamics simulation
Content Type	Audio Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design

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