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.

翻译：翻身是婴儿运动发展中最早期的里程碑之一，反映了全身协调感觉运动控制的出现。本研究利用配备本体感觉和前庭感知的虚拟婴儿身体模型MIMo，对婴儿翻身行为开展计算研究。通过强化学习，MIMo掌握了从仰卧位到俯卧位的滚动技能。值得注意的是，学习到的行为呈现出与真实婴儿报告一致的发展趋势和协调模式，包括随年龄增长表现改善和执行速度加快。我们的研究结果揭示了婴儿能力与身体限制如何催生人工代理中的逼真行为，特别强调了运动发展如何受变化中的身体形态影响。这项工作突出了具身计算模型作为研究感觉运动发展的强大工具的重要作用。