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マニピュレーションarXiv:2412.00597

Spline-FRIDA:多様で人間らしい筆致を実現するサンプル効率の良い微分可能筆ストロークモデル

Spline-FRIDA: Towards Diverse, Humanlike Robot Painting Styles with a Sample-Efficient, Differentiable Brush Stroke Model

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モーションキャプチャで人間の筆致を記録し、オートエンコーダと新たなストローク動力学モデルでロボット描画プラットフォームFRIDAを拡張、より人間らしく芸術的な筆致を生成できるようにした。

著者: Lawrence Chen, Peter Schaldenbrand, Tanmay Shankar, Lia Coleman, Jean Oh

分類: cs.RO

原文アブストラクト

A painting is more than just a picture on a wall; a painting is a process comprised of many intentional brush strokes, the shapes of which are an important component of a painting's overall style and message. Prior work in modeling brush stroke trajectories either does not work with real-world robotics or is not flexible enough to capture the complexity of human-made brush strokes. In this work, we introduce Spline-FRIDA which can model complex human brush stroke trajectories. This is achieved by recording artists drawing using motion capture, modeling the extracted trajectories with an autoencoder, and introducing a novel brush stroke dynamics model to the existing robotic painting platform FRIDA. We conducted a survey and found that our open-source Spline-FRIDA approach successfully captures the stroke styles in human drawings and that Spline-FRIDA's brush strokes are more human-like, improve semantic planning, and are more artistic compared to existing robot painting systems with restrictive B\'ezier curve strokes.

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