Description du projet
Un robot coach pour les personnes âgées
La pratique d’une activité physique chez les personnes âgées leur permet de prévenir de nombreuses maladies et d’améliorer leur qualité de vie. Le projet Dr VCoach, financé par l’UE, va concevoir et déployer un robot coach pour assister les personnes âgées pendant leur entraînement physique quotidien. Plus précisément, le robot comprendra les commandes verbales (par exemple: «Aujourd’hui, je me sens fatigué, pouvons-nous effectuer un entraînement plus léger?»), établira et montrera les exercices à l’utilisateur, surveillera ses performances et suggérera des améliorations. L’ensemble du système sera composé d’un module vocal, d’un planificateur d’exercices, d’un détecteur d’erreurs, d’un module de reconnaissance des actions et d’un module de prédiction. Il utilisera des caméras RVB et des systèmes avancés d’apprentissage profond installés sur un robot humanoïde équipé d’une couche intergicielle qui permettra à des utilisateurs non techniques de le programmer.
Objectif
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).
Champ scientifique
- 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
Programme(s)
Régime de financement
MSCA-IF-EF-ST - Standard EFCoordinateur
09124 Cagliari
Italie