用虚拟婴儿模拟翻身，揭示身体形态如何影响运动发育。
Embodiment Shapes Rolling Behavior in a Multimodal Infant Model
- 构建带本体感觉的虚拟婴儿，通过强化学习学会翻身。
- 模型行为随年龄变化呈现真实婴儿的发育趋势，动作更快更协调。
- 为研究婴幼儿运动发展提供可解释的具身化仿真工具。
翻身是婴儿早期运动发展的关键里程碑，标志着全身协调性感觉运动控制的出现。本文利用具备本体感觉和前庭感知的虚拟婴儿模型MIMo，通过强化学习研究婴儿翻身的计算机制。结果显示，该模型在学习过程中展现出与真实婴儿一致的发展趋势和协调模式，包括随年龄增长表现提升、动作执行速度加快。结果表明，身体形态的变化是驱动运动能力演化的关键因素，验证了具身计算模型在模拟感觉运动发育方面的有效性。这项工作凸显了具身模型作为研究婴幼儿运动发育的强大工具价值。
原文摘要 · Abstract (English)
Rolling over is one of the earliest milestones in infant motor development, reflecting the emergence of coordinated, whole-body sensorimotor control. Here, we conduct a computational study of infant rolling using MIMo, a virtual infant embodiment equipped with proprioception and vestibular sensation. MIMo learns supine-to-prone rolls with reinforcement learning. Interestingly, the learned behaviors capture developmental trends and coordination patterns consistent with those reported in real infants, including improved performance and faster execution with age. Our results explain how infant capabilities and constraints can give rise to realistic behaviors in artificial agents, with a particular emphasis on how motor development is shaped by the changing body morphology. This work highlights the role of embodied computational models as a powerful tool for studying sensorimotor development.
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