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February 28, 2026International Journal of Computational Intelligence Systems0 citationsOpen Access

Three-Dimensional Trajectory Planning for Robotic Chinese Calligraphy: Conforming to Brush Stroke Dynamics

DGDongmei GuoWYWenwen YangWFWenjun Fang

Key Points

  • The aim is to develop a three-dimensional trajectory planning model that adheres to brush calligraphy rules and dynamics.
  • Introduced a spatial trajectory planning model specific to brush calligraphy.
  • Designed an algorithm that accounts for trajectory states, velocity, and acceleration.
  • Conducted experiments to test the performance of the robotic end-effector.
  • Achieved smooth position control during robotic writing operations.
  • Ensured continuous velocity and stable acceleration throughout the writing process.
  • Significantly improved fidelity of calligraphic reproduction in basic strokes compared to existing methods.

Abstract

Trajectory planning is pivotal in intelligent robotic calligraphy, impacting both the process and presentation quality of calligraphic works. Existing methods predominantly focus on two-dimensional trajectories, which inadequately capture the nuances of brush calligraphy. How to obtain the three-dimensional spatial writing trajectories according to the writing rules of brush calligraphy as well as the trajectory state, velocity and acceleration, has become an urgent issue to be addressed. This paper introduces a three-dimensional spatial trajectory planning model tailored to brush calligraphy rules. By designing a spatial trajectory planning algorithm and modeling stroke trajectory states, we account for variations in velocity and acceleration. Experimental results demonstrate certain performance, with smooth position, continuous velocity, and stable acceleration of each stage ensuring seamless writing operations by the robotic end-effector. Compared to other methods, our approach significantly enhances the fidelity of calligraphic reproduction especially in basic strokes. Moreover, our proposed model can conform to brush stroke dynamics.

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Cite This Study

Guo et al. (2026) studied this question.

synapsesocial.com/papers/69a286720a974eb0d3c016bchttps://doi.org/10.1007/s44196-026-01222-1
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