Sustainable Cloud Services for Verbal Interaction with Embodied Agents

TL;DR

This paper introduces a sustainable cloud-based system for verbal interaction with social robots, enabling scalable, background dialogue capabilities and easy integration with various devices through REST APIs, supported by performance assessments.

Contribution

It presents a novel cloud system for autonomous verbal interaction that is adaptable, scalable, and easy to integrate with low-cost robots and devices, enhancing their conversational abilities.

Findings

System supports about 3,000 conversation topics.

Designed for easy expansion via REST APIs.

Performance assessment shows acceptable response times.

Abstract

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.