What Drives You to Interact?: The Role of User Motivation for a Robot in the Wild

TL;DR

This study investigates how different user motivations influence human-robot interaction quality in real-world settings, revealing that motivation-aware robot design can improve engagement and satisfaction.

Contribution

It introduces a field study linking user motivation types with interaction patterns and proposes motivation-informed robot behavior design for better HRI.

Findings

Five interaction fluency patterns identified

Four user motivation types characterized

Motivation-aware design enhances engagement

Abstract

In this paper, we aim to understand how user motivation shapes human-robot interaction (HRI) in the wild. To explore this, we conducted a field study by deploying a fully autonomous conversational robot in a shopping mall over two days. Through sequential video analysis, we identified five patterns of interaction fluency (Smooth, Awkward, Active, Messy, and Quiet), four types of user motivation for interacting with the robot (Function, Experiment, Curiosity, and Education), and user positioning towards the robot. We further analyzed how these motivations and positioning influence interaction fluency. Our findings suggest that incorporating users' motivation types into the design of robot behavior can enhance interaction fluency, engagement, and user satisfaction in real-world HRI scenarios.