Abstract
In this paper, a method based on footprint model and brush trajectory extraction is proposed to make robots write calligraphy. As the footprint model is important for robot calligraphy, especially for the width control of stroke. A footprint model is first proposed based on a binary linear regression algorithm. The relationship between controllable parameters of robot and the width of stroke is established in our model. Thus, the model is suitable for robotic writing. Then, a skeleton-based stroke generation method is proposed for simulating the actual writing process. The writing trajectory of stroke is extracted by the skeleton tracking algorithm, and the normal angle is computed to reconstruct the brush stroke with footprint model and brush trajectory. A writing optimization method based on calligraphic rules is proposed to make strokes conform to calligraphic characteristics. Finally, the Non-Uniform Rational B-Spline (NURBS) algorithm is used for robotic writing path planning so that actual writing could be performed. Our approach shows excellent performance in writing typical strokes and Chinese characters.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (grant No.: 62073249) and Major Project of Hubei Province Technology Innovation (grant No.: 2019AAA071).
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Yan, G., Guo, D., Min, H. (2023). Robot Calligraphy Based on Footprint Model and Brush Trajectory Extraction. In: Sun, F., Cangelosi, A., Zhang, J., Yu, Y., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2022. Communications in Computer and Information Science, vol 1787. Springer, Singapore. https://doi.org/10.1007/978-981-99-0617-8_30
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DOI: https://doi.org/10.1007/978-981-99-0617-8_30
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