Initial Test of "BabyRobot" Behaviour on a Teleoperated Toy Substitution: Improving the Motor Skills of Toddlers

TL;DR

This study introduces 'Baby Robot', an autonomous toy using reinforcement learning and computer vision to enhance motor skills in toddlers, demonstrating significant improvements in real-world kindergarten tests.

Contribution

The paper presents an innovative autonomous toy that actively engages toddlers to improve their motor skills, unlike existing simple, repetitive mobility toys.

Findings

Significant improvement in toddlers' motor skills observed

Robot successfully avoids obstacles and detects children in real environments

Autonomous movement enhances engagement compared to traditional toys

Abstract

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.