Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model
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Abstract (arXiv)
Chinese calligraphy is a unique art form with great artistic value but difficult to master. In this paper, we formulate the calligraphy writing problem as a trajectory optimization problem, and propose an improved virtual brush model for simulating the real writing process. Our approach is inspired by pseudospectral optimal control in that we parameterize the actuator trajectory for each stroke as a Chebyshev polynomial. The proposed dynamic virtual brush model plays a key role in formulating the objective function to be optimized. Our approach shows excellent performance in drawing aesthetically pleasing characters, and does so much more efficiently than previous work, opening up the possibility to achieve real-time closed-loop control.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). First posted on arXiv 2 Mar 2020.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 1.
4 papers.
- 2023Neural Field Dynamics Model for Granular Object Piles Manipulationcited by 6
- 2024CalliRewrite: Recovering Handwriting Behaviors from Calligraphy Images without Supervisioncited by 1
- 2025AnimatePainter: A Self-Supervised Rendering Framework for Reconstructing Painting Processcited by 1
- 2026IMPASTO: Integrating Model-Based Planning with Learned Dynamics Models for Robotic Oil Painting Reproductioncited by 0
- 2026IMPASTO: Integrating Model-Based Planning with Learned Dynamics Models for Robotic Oil Painting Reproduction31 Mar 2026
- 2025AnimatePainter: A Self-Supervised Rendering Framework for Reconstructing Painting Process21 Mar 2025
- 2024CalliRewrite: Recovering Handwriting Behaviors from Calligraphy Images without Supervision20 Mar 2024
- 2023Neural Field Dynamics Model for Granular Object Piles Manipulation1 Nov 2023