S.E.A.G.R: A Socially and Emotionally Aware Greeting Robot Framework with Dual-Layer Cultural and Affective Modulation

2026-07-16

AI Summary

This study addresses the limitation of existing greeting robots in delivering culturally appropriate and emotionally responsive interactions. To overcome this, the authors propose a two-layer modulation framework: the upper layer selects suitable greeting types based on the user’s cultural identity, while the lower layer dynamically adjusts gestures and interpersonal distance using real-time affective cues. Implemented within a Sense-Think-Act architecture, the system integrates a USB camera, ultrasonic sensors, Arduino-controlled servos, and Python-based processing modules to realize a low-cost prototype. The resulting platform demonstrates culturally sensitive and emotion-adaptive social behaviors, providing a proof-of-concept implementation that lays the groundwork for future empirical investigations in human–robot interaction.

Abstract

This paper presents SEAGR (Socially and Emotionally Aware Greeting Robot), a robotic greeting framework designed for human-robot interaction environments involving users from diverse cultural backgrounds and different emotional states. Since greeting behaviour strongly influences first impressions, user comfort, and trust, robots operating in public spaces must be able to interact in a socially appropriate and adaptive manner. However, many existing systems still rely on static greeting routines that do not account for cultural variation, emotional context, or interpersonal distance. SEAGR introduces a dual-layer modulation framework in which cultural identity determines the appropriate greeting type, while affective cues influence how that greeting is executed. The system combines context-aware cultural mapping, emotion-based gesture modulation, and proxemic regulation within a unified Sense-Think-Act architecture. A low-cost prototype is implemented using a USB camera, ultrasonic sensor, Arduino-controlled servos, and a laptop-based Python processing system. This work is presented as a system design and proof-of-concept; empirical validation through user studies is explicitly acknowledged as a current limitation and is identified as the primary direction for future work.

Problem

• human-robot interaction
• cultural variation
• emotional context
• greeting behavior
• social appropriateness

Innovation

• dual-layer modulation
• cultural adaptation
• affective computing
• proxemic regulation
• socially aware robotics