Initial Test of "BabyRobot" Behaviour on a Teleoperated Toy Substitution: Improving the Motor Skills of Toddlers
This addresses motor skill development for toddlers, but it is incremental as it builds on existing commercial toys by adding intelligent autonomous movement.
The authors tackled the problem of improving toddlers' motor skills by developing 'Baby Robot', a car-like toy that uses reinforcement learning and computer vision to move autonomously and escape from detected babies while avoiding obstacles. In real-world experiments in a kindergarten, the robot led to significant improvements in participants' motion skills compared to regular toys.
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.