AI 中文总结
本文针对现有角色控制器缺乏生物力学先验导致动作不自然的问题，提出引入疲劳作为有限能量上限，结合三分区控制器模型实现不同疲劳状态下的动作模仿，可提升角色动画的自然度等性能。
AI 中文摘要
用物理仿真复现人类行为是角色动画领域长期以来的目标，现有研究在模仿各类通用动作方面已取得出色性能，但多数研究因缺乏生物力学与生理学先验，仍存在动作不自然的问题。鉴于此，本文关注行为能量学的进展，该领域揭示能量消耗如何塑造人类动作；而当前角色控制器通常假设角色拥有无限能量，这与实际情况不符。受此启发，本文提出将疲劳作为有限能量上限的替代指标，将其引入通用角色动画，并深入研究疲劳如何为基于物理的角色控制带来新特性。本文利用三分区控制器（Three-Compartment Controller, 3CC）模型，成功获取不同疲劳状态下通用动作模仿的策略，还开展了大量分析以证明疲劳可影响角色动画的自然度、可扩展性与鲁棒性，本文代码将公开。
英文摘要
Replicating human behavior with physics simulation has been a long-expected goal in character animation. Existing efforts have achieved impressive performance in imitating a wide span of general motions. However, most existing efforts could still suffer from unnatural movements due to the lack of biomechanical and physiological priors. Given this, we project our sights to advances in behavioral energetics, which demonstrate how energy use shapes human movements. In contrast, current character controllers typically assume the character is equipped with infinite energy over time. Inspired by these, we propose to adopt fatigue as a proxy of the finite energy limit, inject it into general character animation, and thoroughly investigate how fatigue introduces new characteristics to physics-based character control. Leveraging the Three-Compartment Controller (3CC) model, we managed to obtain a policy for general motion imitation under different fatigue statuses. Furthermore, extensive analyses are conducted to demonstrate how fatigue could influence the naturalness, scalability, and robustness of character animation. Our code will be made public.
Comments14 pages, 13 figures
