TeachingBot: Robot Teacher for Human Handwriting

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Authors: Zhimin Hou, Cunjun Yu, David Hsu, Haoyong Yu
Cited by: 2
References: 26

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 presentsTeachingBot, 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 human learner and (ii) maintaining an engaging learning experience. For the first challenge, TeachingBot uses a probabilistic model to capture the human 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 human learner's natural writing. For the second challenge, TeachingBot employs variable impedance control to guide the human learner, dynamically adjusting the strength of physical guidance based on the human learner's writing performance. Human-subject experiments demonstrate the effectiveness of TeachingBot, showing clear improvement in learners' handwriting and engagement over baseline methods.

Fields of Study & Subjects

Robot Manipulation and Learning Social Robot Interaction and HRI Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
11
Issue
3
Pages
2610–2617
Publication date
12 January 2026