TeachingBot: Robot Teacher for Human Handwriting

TL;DR

TeachingBot is an adaptive robot system that personalizes handwriting instruction through probabilistic modeling and variable impedance control, significantly improving learning outcomes and engagement.

Contribution

This work introduces a novel robotic teaching system that personalizes handwriting instruction by modeling individual styles and dynamically adjusting physical guidance.

Findings

Learners showed improved handwriting quality after training with TeachingBot.

Participants reported higher engagement levels compared to baseline methods.

The system effectively adapts to individual handwriting styles.

Abstract

Teaching and learning physical skills often require one-on-one interaction, making it difficult to scale up, as there are not enough human teachers. Robots offer an attractive alternative. This paper presents TeachingBot, an adaptive robotic system that teaches handwriting to human learners through physical interaction. Robot teaching poses two major challenges: (i) adapting to the individual handwriting style of the learner and (ii) maintaining an engaging learning experience. For the first challenge, TeachingBot uses a probabilistic model to capture the learner's writing style from their writing samples. Drawing on the insight that effective teaching balances standardization with individuality, the system generates a personalized teaching trajectory that aligns with the learner's natural writing. For the second challenge, TeachingBot employs variable impedance control to guide the learner, dynamically adjusting the strength of physical guidance based on the learner's performance. Human-subject experiments with 15 participants demonstrate the effectiveness of TeachingBot, showing clear improvement in learners' handwriting and engagement over baseline methods.