2014 RSS RSS 2014

Modeling and Controlling Friendliness for An Interactive Museum Robot

Abstract

Advances in robotic technologies have enabled interactive robots to utilize humanlike social behaviors to interact with people in public places such as museums. While these behaviors have shown promise in engaging people, they have been designed and applied to users uniformly. Humans, however, behave differently according to their relationships with others. Behavioral changes, from neutral to friendly, contribute to the development of interpersonal relationships. Friendliness, in particular, plays an important role in the early development of a relationship. In this work, we explore how an interactive robot might nonverbally express a variety of friendly behaviors in a museum scenario. Four behavioral variables—response time, approach speed, individual distance, and attentiveness—contributing to perceived friendliness were modeled and implemented for the interactive museum robot. The results of our study showed that people perceived the differences in the designed robot behaviors and related those differences to the friendliness of the robot to varying degrees. This work serves as a building block toward the development of human-robot relationships and has implications on designing friendly behaviors for interactive robots.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Reinforcement Learning
📈 Trend Setter — Human-AI Interaction
🧭 Keyword Pioneer — friendliness modeling
🐝 Cross-Pollinator — Artificial Intelligence, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
🐣 Hot Topic Early Bird — human-robot interaction