Descrizione del progetto
Un robot allenatore per gli anziani
L’attività fisica per gli anziani previene numerose malattie e migliora la qualità della vita. Il progetto Dr VCoach, finanziato dall’UE, progetterà e distribuirà un allenatore robotico per assistere gli anziani durante l’allenamento fisico quotidiano. In particolare, il robot sarà in grado di comprendere comandi vocali (ad esempio, «Oggi mi sento stanco, possiamo fare un allenamento più leggero?»), definire e mostrare gli esercizi all’utente, monitorare le prestazioni e suggerire miglioramenti. L’intero sistema sarà composto da un modulo vocale, un programmatore di esercizi, un rilevatore di errori, un modulo di riconoscimento e un modulo di previsione delle azioni. Utilizzerà telecamere RGB e sistemi avanzati di apprendimento profondo implementati su un robot umanoide dotato di uno strato di middleware che lo rende programmabile da utenti privi di competenze tecniche.
Obiettivo
The main objective of this project (DR VCoach) will be the following: “Design and implement a robotic coach able to propose a proper exercise schedule based on human directives, monitor the exercise performed by the patient/elder and correct it in case of mistakes”. The output of the project will be a robotic coach to assist the elders during their daily physical training. The robot will be able to understand verbal commands from the user (e.g. what will be the training schedule of today? Today I feel tired, can we do a lighter training?), to define the sequence of exercises to be performed, to show the exercises to the user (with a verbal description and performing them by it-self), to monitor the user performing the exercises using RGB cameras, to eventually find some errors in the execution and to suggest a correction to the mistake.
The whole system can be divided into four modules:
- Speech module: This is the module in charge of the vocal interaction between the robot and the elders.
- Exercise scheduler: The role of this module is to break the selected exercise into atomic actions, and send these actions to the Error detector and Action recognition and prediction modules.
- Error detector: The Error detector module analyses the results coming from the Action recognition and prediction module based on the required actions received by the Exercise scheduler. After evaluating the performed action, the module sends an evaluation report to the speech module in order to inform the elder.
- Action recognition and prediction: This module has the dual task of recognising the action performed by the elder using the RGB videos coming from its embedded camera, and predicting the future viso-proprioceptive stimuli based on the action that is being performed.
The system will be implemented on Zora (a NAO robot with a software layer to make it usable by non ICT people).
Campo scientifico
- natural sciencescomputer and information sciencessoftware
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- social scienceseconomics and businessbusiness and managementemployment
Programma(i)
Argomento(i)
Meccanismo di finanziamento
MSCA-IF-EF-ST - Standard EFCoordinatore
09124 Cagliari
Italia