SketcherX: AI-Driven Interactive Robotic drawing with Diffusion model and Vectorization Techniques
On the map: Diffusion models → Image generation, text-to-image and editing
Abstract (arXiv)
We introduce SketcherX, a novel robotic system for personalized portrait drawing through interactive human-robot engagement. Unlike traditional robotic art systems that rely on analog printing techniques, SketcherX captures and processes facial images to produce vectorized drawings in a distinctive, human-like artistic style. The system comprises two 6-axis robotic arms : a face robot, which is equipped with a head-mounted camera and Large Language Model (LLM) for real-time interaction, and a drawing robot, utilizing a fine-tuned Stable Diffusion model, ControlNet, and Vision-Language models for dynamic, stylized drawing. Our contributions include the development of a custom Vector Low Rank Adaptation model (LoRA), enabling seamless adaptation to various artistic styles, and integrating a pair-wise fine-tuning approach to enhance stroke quality and stylistic accuracy. Experimental results demonstrate the system's ability to produce high-quality, personalized portraits within two minutes, highlighting its potential as a new paradigm in robotic creativity. This work advances the field of robotic art by positioning robots as active participants in the creative process, paving the way for future explorations in interactive, human-robot artistic collaboration.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 8 of its 13 references that are in the map. First posted on arXiv 4 Sep 2024.
Builds on
8 of 13 references.
Closest ancestors · 2
Same direction, newest first
- 2023Adding Conditional Control to Text-to-Image Diffusion Models10 Feb
- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation25 Aug
Other references · 6
- 2023GPT-4 Technical Reportcited by 18,396
- 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
- 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,937
- 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 991
- 2024DeepSeek-VL: Towards Real-World Vision-Language Understandingcited by 733
- 2022FRIDA: A Collaborative Robot Painter with a Differentiable, Real2Sim2Real Planning Environmentcited by 18
Built on by
Citing papers per year: 2025: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
- 2026An Embodied Companion for Visual Storytelling
- 2024SketchAgent: Language-Driven Sequential Sketch Generation
- 2025SwiftSketch: A Diffusion Model for Image-to-Vector Sketch Generation
- 2025SakugaFlow: A Stagewise Illustration Framework Emulating the Human Drawing Process and Providing Interactive Tutoring for Novice Drawing Skills
- 2024It's All About Your Sketch: Democratising Sketch Control in Diffusion Models
- 2026PaintCopilot: Modeling Painting as Autonomous Artistic Continuation
- 2024Deep Robot Sketching: An application of Deep Q-Learning Networks for human-like sketching
- 2023Conditional Human Sketch Synthesis with Explicit Abstraction Control