Robotic Rendering of Oriental Ink Paintings with Spatial Awareness
Shaojun Hu, Zhiqi Yan, Yuhao Liu, Hao Jin, Minghui Lian, Zhiyi Zhang
AI summary
Problem
Physically rendering stylized oriental ink paintings from 3D environments remains difficult due to the complex abstraction of spatial geometry into traditional brushstrokes and shading techniques. Existing methods lack automated, spatially-aware pipelines that faithfully mimic the material and stylistic nuances of real artists.
Approach
The authors develop a pipeline that extracts contours and generates line strokes from 3D models using B-spline fitting and isophote distances, applies oriented Poisson disk sampling for dot shading, and maps the results to a robotic arm on guide rails for large-scale canvas painting.
Key results
- Automated spatially-aware pipeline for large-scale Shuimohua robotic painting
- Fast skeleton-based contour vectorization with clamped B-spline and isophote thickness control
- Oriented Poisson disk sampling method for artistically faithful dot shading
- Successful physical rendering of diverse 3D models on rice paper using a consumer-grade robot
Why it matters
Enables automated, culturally authentic physical art creation from 3D data, advancing human-robot interaction and digital heritage preservation.
Abstract
Enabling robots to imitate artists who observe objects in the 3D world and physically draw them in a specific style is a challenging problem. Shuimohua (Sumi-e) is a typical non-photorealistic oriental ink painting art that uses simple ink, water and brush to paint and convey poetic imagery. Although digital rendering of non-photorealistic paintings has been extensively studied, physical rendering of stylized painting from 3D space is still a challenge because it requires to consider the abstraction process of vectorized strokes with various styles in physical environment. In this paper, we propose a robotic rendering approach for physically drawing oriental ink painting from 3D shapes, and aim to mimic the painting process of a real-world artist using binocular vision to estimate 3D scenes. By referring to the artists’ drawing habit, first, we extract expressive contours as drawing outlines and vectorize the contours to polylines. Next, the polylines are converted to line strokes with varying thicknesses by considering clamped B- spline fitting and isophote distances. In order to generate a typical dot shading effect, an oriented Poisson disk sampling approach is proposed to create dot strokes to depict the internal features of the 3D Shapes. Finally, we build an ink gradient model and map the coordinates of the strokes to a robotic arm, and a control method of guide rails is proposed for robotic painting on large canvases.