JUNO Project: Deployment and Validation of a Low-Cost Cloud-Based Robotic Platform for Reliable Smart Navigation and Natural Interaction with Humans in an Elderly Institution

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 1; p. 483
• Main Authors: Pavón-Pulido, Nieves, Blasco-García, Jesús Damián, López-Riquelme, Juan Antonio, Feliu-Batlle, Jorge, Oterino-Bono, Roberto, Herrero, María Trinidad
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.01.2023; MDPI
• Subjects: Aged; Artificial intelligence; autonomous navigation; Caregivers; Cloud Computing; Cognitive ability; Communication; Computational linguistics; COVID-19 vaccines; Deep learning; Dementia; digital transformation of health systems; Digitization; Exercise; Humans; human–robot natural interaction; Internet of Things; Language processing; Lifestyles; Machine learning; Natural language interfaces; Natural Language Processing; Older people; Pandemics; Quality of life; Robotic Surgical Procedures; Robotics; Robotics - methods; Robots; Sensors; smart assistant robots; Social networks; User interface; Spain; human–robot natural interaction; autonomous navigation; digital transformation of health systems; smart assistant robots
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23010483

This paper describes the main results of the JUNO project, a proof of concept developed in the Region of Murcia in Spain, where a smart assistant robot with capabilities for smart navigation and natural human interaction has been developed and deployed, and it is being validated in an elderly institution with real elderly users. The robot is focused on helping people carry out cognitive stimulation exercises and other entertainment activities since it can detect and recognize people, safely navigate through the residence, and acquire information about attention while users are doing the mentioned exercises. All the information could be shared through the Cloud, if needed, and health professionals, caregivers and relatives could access such information by considering the highest standards of privacy required in these environments. Several tests have been performed to validate the system, which combines classic techniques and new Deep Learning-based methods to carry out the requested tasks, including semantic navigation, face detection and recognition, speech to text and text to speech translation, and natural language processing, working both in a local and Cloud-based environment, obtaining an economically affordable system. The paper also discusses the limitations of the platform and proposes several solutions to the detected drawbacks in this kind of complex environment, where the fragility of users should be also considered.