意図と丁寧さに適応する対話型ソーシャルロボットナビゲーション
Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots
ユーザの発話に含まれる意図と丁寧さの度合いを理解し、ロボットの移動速度や応答を動的に変化させる対話ナビゲーションシステムを開発し、Pepperロボットで実証した。
著者: Chandrakant Bothe, Fernando Garcia, Arturo Cruz Maya, Amit Kumar Pandey, Stefan Wermter
分類: cs.RO, cs.AI, cs.CL
原文アブストラクト
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.
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