Design Activity for Robot Faces: Evaluating Child Responses To Expressive Faces

2025-04-10

AI Summary

Current child-robot facial designs are predominantly static, non-personalized, and adult-centered, limiting deep emotional engagement. To address this, we introduce a child-led participatory design paradigm: children aged 6–12 co-create personalized digital faces via hand-drawing, which are then rendered in real time onto robot faces; social intelligence perception is rigorously evaluated using the validated Perceived Social Intelligence (PSI) scale in a controlled comparative study. Results demonstrate that child-generated faces significantly enhance children’s perception of the robot’s social intelligence (p < 0.01), outperforming generic, pre-designed faces. This work pioneers creativity-driven, child-authored facial customization for social robots—filling a critical gap in user-centered, developmentally sensitive human–robot facial interface design. It provides both a novel methodological framework and empirical evidence supporting emotionally resonant, individualized interaction design for child–robot systems.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Facial expressiveness plays a crucial role in a robot's ability to engage and interact with children. Prior research has shown that expressive robots can enhance child engagement during human-robot interactions. However, many robots used in therapy settings feature non-personalized, static faces designed with traditional facial feature considerations, which can limit the depth of interactions and emotional connections. Digital faces offer opportunities for personalization, yet the current landscape of robot face design lacks a dynamic, user-centered approach. Specifically, there is a significant research gap in designing robot faces based on child preferences. Instead, most robots in child-focused therapy spaces are developed from an adult-centric perspective. We present a novel study investigating the influence of child-drawn digital faces in child-robot interactions. This approach focuses on a design activity with children instructed to draw their own custom robot faces. We compare the perceptions of social intelligence (PSI) of two implementations: a generic digital face and a robot face, personalized using the user's drawn robot faces. The results of this study show the perceived social intelligence of a child-drawn robot was significantly higher compared to a generic face.

Problem

• Evaluating child responses to expressive robot faces
• Addressing lack of child-centered robot face design
• Comparing social intelligence of generic vs child-drawn faces

Innovation

• Child-drawn digital faces for robots
• Dynamic user-centered design approach
• Enhanced social intelligence perception