This article introduces "Baby Robot", a robot aiming to improve motor skills of babies and toddlers. Authors developed a car-like toy that moves autonomously using reinforcement learning and computer vision techniques. The robot behaviour is to escape from a target baby that has been previously recognized, or at least detected, while avoiding obstacles, so that the security of the baby is not compromised. A myriad of commercial toys with a similar mobility improvement purpose are into the market; however, there is no one that bets for an intelligent autonomous movement, as they perform simple yet repetitive trajectories in the best of the cases. Two crawling toys -- one in representation of "Baby Robot" -- were tested in a real environment with respect to regular toys in order to check how they improved the toddlers mobility. These real-life experiments were conducted with our proposed robot in a kindergarten, where a group of children interacted with the toys. Significant improvement in the motion skills of participants were detected.

翻译：本文介绍了一种名为"婴儿机器人"的机器人，旨在提升婴儿和幼儿的运动技能。作者开发了一种类车玩具，利用强化学习和计算机视觉技术实现自主移动。该机器人的行为模式是：在避开障碍物的同时，逃离先前识别（或至少检测到）的目标婴儿，以确保婴儿的安全。市场上已有大量旨在提升运动能力的类似商业玩具，但尚无一款玩具采用智能自主运动方案——它们最多只能执行简单重复的轨迹。为验证其对幼儿运动能力的改善效果，我们以两款爬行玩具（其中一款代表"婴儿机器人"）作为实验组，在真实环境中与常规玩具进行对比测试。这些真实场景实验在幼儿园开展，让一组儿童与玩具互动。检测结果表明，参与者的运动技能得到了显著提升。