Sentiment-based Engagement Strategies for intuitive Human-Robot Interaction

TL;DR

This paper explores sentiment-based engagement strategies in human-robot interaction, using emotion detection to adapt robot behavior for more intuitive and mutually understandable interactions.

Contribution

It introduces four novel engagement strategies that incorporate emotion and attention cues, implemented on a mobile robot platform for initial testing.

Findings

Effective emotion detection for interaction adaptation

Improved mutual understanding in human-robot interactions

Feasibility of sentiment-based engagement strategies

Abstract

Emotion expressions serve as important communicative signals and are crucial cues in intuitive interactions between humans. Hence, it is essential to include these fundamentals in robotic behavior strategies when interacting with humans to promote mutual understanding and to reduce misjudgements. We tackle this challenge by detecting and using the emotional state and attention for a sentiment analysis of potential human interaction partners to select well-adjusted engagement strategies. This way, we pave the way for more intuitive human-robot interactions, as the robot's action conforms to the person's mood and expectation. We propose four different engagement strategies with implicit and explicit communication techniques that we implement on a mobile robot platform for initial experiments.