RoboLinker: A Diffusion-model-based Matching Clothing Generator Between Humans and Companion Robots

2025-08-01

AI Summary

Addressing the growing need for human-robot aesthetic collaboration, this work tackles the challenge of generating visually harmonious and emotionally resonant clothing pairings between humans and heterogeneous companion robots (e.g., humanoid and pet-like). Method: We propose the first diffusion-based framework integrating cross-modal style understanding and an interactive optimization interface. Given a user’s textual style prompt and a robot image, our method jointly generates matched human-robot attire that ensures stylistic consistency and affective alignment. Contribution/Results: (1) First method enabling co-generation of coordinated outfits across morphologically distinct robot types and humans; (2) A novel empathic design paradigm balancing visual coherence and emotional resonance; (3) An interactive interface supporting real-time user feedback and iterative refinement. Extensive evaluation demonstrates significant improvements over baselines in outfit diversity, cross-modal consistency, and user satisfaction.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Interaction Techniques and Devices
• Computer Vision: Diffusion Models for Vision

Application Category

• Economics, Online Markets and Human Computation: Humans versus LLMs for data annotation and labeling
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

We present RoboLinker, a generative design system that creates matching outfits for humans and their robots. Using a diffusion-based model, the system takes a robot image and a style prompt from users as input, and outputs a human outfit that visually complements the robot's attire. Through an interactive interface, users can refine the generated designs. We evaluate RoboLinker with both humanoid and pet-like robots, demonstrating its capacity to produce stylistically coherent and emotionally resonant results.

Problem

• Generates matching outfits for humans and robots
• Uses diffusion model for style-based clothing design
• Evaluates design coherence across robot types

Innovation

• Diffusion-model-based clothing generator
• Interactive outfit design refinement
• Human-robot style matching system