Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots

TL;DR

This paper presents a novel dialogue system for social robots that dynamically adapts navigation behaviour based on user intention and politeness, enhancing social interaction in indoor environments.

Contribution

It introduces a method to incorporate politeness cues into robotic dialogue systems to modulate navigation and responses based on user social cues.

Findings

Robot adapts navigation speed based on politeness cues.

System successfully modulates responses according to user intention.

Demonstrated with Pepper robot in indoor navigation tasks.

Abstract

Service robots need to show appropriate social behaviour in order to be deployed in social environments such as healthcare, education, retail, etc. Some of the main capabilities that robots should have are navigation and conversational skills. If the person is impatient, the person might want a robot to navigate faster and vice versa. Linguistic features that indicate politeness can provide social cues about a person's patient and impatient behaviour. The novelty presented in this paper is to dynamically incorporate politeness in robotic dialogue systems for navigation. Understanding the politeness in users' speech can be used to modulate the robot behaviour and responses. Therefore, we developed a dialogue system to navigate in an indoor environment, which produces different robot behaviours and responses based on users' intention and degree of politeness. We deploy and test our system with the Pepper robot that adapts to the changes in user's politeness.