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arXiv 2203.02606cs.RO
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用于与具身智能体进行口头交互的可持续云服务

Sustainable Cloud Services for Verbal Interaction with Embodied Agents

University of Genoa(热那亚大学)

Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

摘要:

本文介绍了一个基于知识的自主互动的社交机器人和其他会话代理的云系统的设计和实现。该系统对于低成本的机器人和设备特别方便:它可以用作独立的对话系统,也可以作为一个集成,为机器人可能已经具备的任何预先存在的自然语言处理能力提供“后台”对话能力,作为其基本技能的一部分。通过连接到云,开发人员可以通过网络连接管理口头交互,大约有3,000个对话主题可以“闲聊”,还有一个预先准备好的计划库,只需要根据机器人的物理能力。该系统被构造为一组REST API端点,因此可以通过添加新的API来轻松扩展,以提高连接到云的客户端的功能。该系统的另一个关键特征是,它的设计使其客户端的开发变得简单明了:通过这种方式,多个机器人和设备可以轻松地被赋予与用户自主交互的能力,了解何时执行特定操作,并利用云服务提供的所有信息。本文概述并讨论了实验结果,以评估系统的性能方面的响应时间,铺平了道路,其使用的研究和市场解决方案。ROS和流行机器人(如Pepper和NAO)的客户端存储库链接可应要求提供。

英文摘要:

This article presents the design and the implementation of a cloud system for knowledge-based autonomous interaction devised for Social Robots and other conversational agents. The system is particularly convenient for low-cost robots and devices: it can be used as a stand-alone dialogue system or as an integration to provide "background" dialogue capabilities to any preexisting Natural Language Processing ability that the robot may already have as part of its basic skills. By connecting to the cloud, developers are provided with a sustainable solution to manage verbal interaction through a network connection, with about 3,000 topics of conversation ready for "chit-chatting" and a library of pre-cooked plans that only needs to be grounded into the robot's physical capabilities. The system is structured as a set of REST API endpoints so that it can be easily expanded by adding new APIs to improve the capabilities of the clients connected to the cloud. Another key feature of the system is that it has been designed to make the development of its clients straightforward: in this way, multiple robots and devices can be easily endowed with the capability of autonomously interacting with the user, understanding when to perform specific actions, and exploiting all the information provided by cloud services. The article outlines and discusses the results of the experiments performed to assess the system's performance in terms of response time, paving the way for its use both for research and market solutions. Links to repositories with clients for ROS and popular robots such as Pepper and NAO are available on request.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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