Human-Robot Interaction Study
Comprehensive study on natural language interaction with Pepper humanoid robot, analyzing human behavior patterns and trust factors
Project Overview
Challenge
Understanding how humans naturally interact with AI systems through voice and identifying the key factors that build trust with social robots in academic environments.
Solution
Programmed Pepper humanoid robot for natural language interactions and conducted comprehensive field studies at university entrance, analyzing human behavior patterns and emotional responses.
Key Features
Results & Impact
Successfully analyzed data from 99 participants and 16 detailed interviews to identify key behavioral patterns and trust factors for social robot adoption. Research accepted for publication at OzCHI 2025.
Technology Stack
AI & ML
Backend
System Architecture
Data Processing
Natural language understanding and dialogue management
AI Engine
Robot control systems with speech recognition
User Interface
Physical robot interaction with voice commands
Innovation
Comprehensive study on human-robot trust factors in natural campus environments.
Performance
Large-scale study with 99 participants and 16 detailed interviews for comprehensive insights.
Impact & Results
Project Impact
Successfully analyzed data from 99 participants and 16 detailed interviews to identify key behavioral patterns and trust factors for social robot adoption. Research accepted for publication at OzCHI 2025.
Key Achievements:
Future Impact
Insights from this study will guide the development of more trustworthy social robots in academic and public environments.