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DTSTAMP:20260114T163633Z
LOCATION:Darling Harbour Theatre\, Level 2 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T093000
DTEND;TZID=Australia/Melbourne:20231212T124500
UID:siggraphasia_SIGGRAPH Asia 2023_sess209_papers_178@linklings.com
SUMMARY:MuscleVAE: Model-Based Controllers of Muscle-Actuated Characters
DESCRIPTION:Yusen Feng, Xiyan Xu, and Libin Liu (Peking University)\n\nIn 
 this paper, we present a simulation and control framework for generating b
 iomechanically plausible motion for muscle-actuated characters. We incorpo
 rate a fatigue dynamics model, the 3CC-r model, into the widely-adopted Hi
 ll-type muscle model to simulate the development and recovery of fatigue i
 n muscles, which creates a natural evolution of motion style caused by the
  accumulation of fatigue from prolonged activities. To address the challen
 ging problem of controlling a musculoskeletal system with high degrees of 
 freedom, we propose a novel muscle-space control strategy based on PD cont
 rol. Our simulation and control framework facilitates the training of a ge
 nerative model for muscle-based motion control, which we refer to as Muscl
 eVAE. By leveraging the variational autoencoders (VAEs), MuscleVAE is capa
 ble of learning a rich and flexible latent representation of skills from a
  large unstructured motion dataset, encoding not only motion features but 
 also muscle control and fatigue properties. We demonstrate that the Muscle
 VAE model can be efficiently trained using a model-based approach, resulti
 ng in the production of high-fidelity motions and enabling a variety of do
 wnstream tasks.\n\nRegistration Category: Full Access, Enhanced Access, Tr
 ade Exhibitor, Experience Hall Exhibitor\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_178&sess=sess209
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