Adaptive Child-Robot Interaction: Enhancing Educational Outcomes through Applied Behavior Analysis and Real-Time Replanning

This paper introduces a robotic system architecture for behavior management in educational settings, inspired by Applied Behavior Analysis (ABA). The system utilizes a socially assistive robot (SAR) that autonomously delivers educational activities, monitors behavior, and proposes management strategies using the Planning Domain Definition Language (PDDL) framework. By integrating cloud-based processing with local execution, the robot adapts in real-time to enhance social interactions. The study outlines future works, including an experimental protocol designed to enhance the management of children’s behavior during child-robot interactions.