Collision-aware interactive simulation using graph neural networks.
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ABSTRACT:
SUBMITTER: Zhu X
PROVIDER: S-EPMC9170855 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Publications
Collision-aware interactive simulation using graph neural networks.
Zhu Xin X Qian Yinling Y Wang Qiong Q Feng Ziliang Z Heng Pheng-Ann PA
Visual computing for industry, biomedicine, and art 20220607 1
Deep simulations have gained widespread attention owing to their excellent acceleration performances. However, these methods cannot provide effective collision detection and response strategies. We propose a deep interactive physical simulation framework that can effectively address tool-object collisions. The framework can predict the dynamic information by considering the collision state. In particular, the graph neural network is chosen as the base model, and a collision-aware recursive regre ...[more]
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