Enhancing Telepresence Robots with AI: Combining Services to Personalize and React

Abstract

Mobile Telepresence Robots represent a class of robotic platforms, characterized by a video conferencing system mounted on a mobile robotic base, which allows a pilot user to move around in the robot’s environment. These commercially available platforms are relatively cheap and straightforward, yet robust enough to operate continuously in a dynamic environment. Their simplicity and robustness make them particularly suitable for the application in an elderly care context. Although the technology used on these robotic platforms has evolved considerably in recent years, these tools are meant to have no or minimal autonomy and are, hence, mostly relegated to provide pure telepresence services for video calls between the older users and their carers. This work aims to lay the foundations to increase the autonomy of mobile telepresence robots, both by supporting teleoperation through shared approaches and offering services to users in total autonomy. To this purpose, different artificial intelligence technologies such as Reasoning, Knowledge Representation, Automated Planning, Machine Learning, Natural Language Processing, Advanced Perception and Navigation must coexist on limited hardware. An architecture aiming to integrate these technologies is proposed together with backbone services that integrate classical and innovative AI with robotics. Additionally, the problems that arise from the integration of heterogeneous technologies such as plan adaptation needs, shared navigation challenges and the generation of data-driven models able to run on not-performant hardware, are presented along with possible solutions exemplified on the older users assistance domain.