Stroke-based modeling and haptic skill display for Chinese calligraphy simulation system

The goal of this paper is to study haptic skill representation and display in a Chinese calligraphy training system. The challenge is to model haptic skill during the writing of different strokes in Chinese characters and to achieve haptic rendering with high fidelity and stability. The planning of the writing process is organized at three levels: task, representation and device level to describe the haptic handwriting skill. State transition graph (STG) is proposed to describe switches between tasks during the handwriting. Chinese characters are modeled using 39 typical strokes, which are further grouped into basic and compound strokes. The compound stroke is considered to be sequential combination of the basic strokes. Straight and curve strokes are modeled using line segment and the Bezier curve, respectively. Information from STG is used for real-time collision detection and haptic rendering. Ambiguity of the collision detection at stroke-corner points is prevented using active stroke combined with local nearest point computation. A modified virtual fixture method is developed for haptic rendering. The approach is tested on a prototype training system using Phantom desktop. Initial experiments suggest that the proposed modeling and rendering method is effective.