This article presents the design and the implementation of CAIR: 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 CAIR, 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 given.
翻译:本篇文章介绍了CAIR的设计和实施:为社会机器人和其他对话代理人设计的基于知识的自主互动的云层系统。这个系统对于低成本机器人和设备来说特别方便:它可以作为一个独立的对话系统或集成使用,为机器人可能已经具备的自然语言处理能力提供“背景”对话能力,作为基本技能的一部分。通过连接CAIR,为开发商提供了一个可持续的解决方案,通过网络连接管理口头互动,大约3 000个对话主题为社会机器人和其他对话代理商准备就绪,并有一个预制计划的图书馆,只需要以机器人的物理能力为基础。这个系统的结构可以作为一套REST API终端点,以便通过添加新的API来提高机器人可能已经具备的自然语言处理能力。这个系统的另一个关键特征是,它的设计是为了使其客户的发展变得简单明了:通过这种方式,多个机器人和装置可以很容易地与用户自主地进行互动,了解何时可以进行具体的操作,如何扩大它的范围,从而能够通过新的APIER系统来提高客户的能力,并且利用它所运行的云路路路流,并且通过运行的路径来评估其运行结果。