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Towards Dialogue-Based Navigation with Multivariate Adaptation Driven by Intention and Politeness for Social Robots

机译:在社会机器人的意图和礼貌推动的基于对话的导航与多变量适应的导航

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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.
机译:服务机器人需要表现出适当的社会行为,以便在医疗保健,教育,零售等社会环境中部署一些机器人应该具有导航和会话技能的一些主要能力。如果此人不耐烦,则该人可能希望机器人更快地导航,反之亦然。语言特征,表明礼貌可以为一个人的患者和不耐烦行为提供社会案例。本文呈现的新颖性是动态地在机器人对话系统中动态地纳入导航。了解用户语音的礼貌可用于调制机器人行为和响应。因此,我们开发了一个对话系统,可以在室内环境中导航,这基于用户的意图和礼貌程度产生不同的机器人行为和响应。我们用辣椒机器人部署和测试我们的系统,这些机器人适应用户礼貌的变化。

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