Collision-aware interactive simulation using graph neural networks

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 coll...

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Detalles Bibliográficos
Autores principales: Zhu, Xin, Qian, Yinling, Wang, Qiong, Feng, Ziliang, Heng, Pheng-Ann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170855/
https://www.ncbi.nlm.nih.gov/pubmed/35668216
http://dx.doi.org/10.1186/s42492-022-00113-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170855/
https://www.ncbi.nlm.nih.gov/pubmed/35668216
http://dx.doi.org/10.1186/s42492-022-00113-4

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