Dance Teaching by a Robot: Combining Cognitive and Physical Human-Robot Interaction for Supporting the Skill Learning Process

TL;DR

This paper introduces a robot-based dance teaching system that combines cognitive and physical interaction, using adaptive control and performance scoring to enhance skill learning and user experience.

Contribution

It presents a novel adaptive impedance controller and a progressive teaching scoring system for robot-assisted dance training.

Findings

PT improves early skill acquisition.

Subjects preferred PT over baseline in comfort and perception.

Adaptive control enhances human-robot interaction quality.

Abstract

This letter presents a physical human-robot interaction scenario in which a robot guides and performs the role of a teacher within a defined dance training framework. A combined cognitive and physical feedback of performance is proposed for assisting the skill learning process. Direct contact cooperation has been designed through an adaptive impedance-based controller that adjusts according to the partner's performance in the task. In measuring performance, a scoring system has been designed using the concept of progressive teaching (PT). The system adjusts the difficulty based on the user's number of practices and performance history. Using the proposed method and a baseline constant controller, comparative experiments have shown that the PT presents better performance in the initial stage of skill learning. An analysis of the subjects' perception of comfort, peace of mind, and robot performance have shown a significant difference at the p < .01 level, favoring the PT algorithm.