Obiettivo Physical disabilities due to illness, injury, or ageing can alter the way a person moves around the house, manipulates objects and senses their home. These issues make it harder for persons to execute daily home activities on their own, and therefore specialized professionals are required to take care of them. However, the growing elderly population and the persons having basic activity difficulties or suffering from long-standing diseases are saturating the health systems due to insufficient infrastructures and over-demand for health carers. Robotics-based solutions are a promising alternative to support the human labour at health care. This project focuses on how robotic assistants can be exploited to provide independence and empower people with different kinds of mobility problems. Specifically, the main goal is to assist these persons in dressing themselves, which has been found to be an important task for independent living. In this sense, a robotic dressing assistant needs to skilfully manipulate clothes, physically interact with the human, recognize his/her intentions and actions, and easily adapt to changes in the clothing, user posture, and degree of mobility of the assisted person. These highly complex features are tackled in this proposal from a robot learning perspective, in which programming-by-demonstration, reinforcement and interactive learning will be combined to create both sophisticated manipulation skills and safe assistance behaviours. The proposal envisions three different real experimental scenarios to test the proposed approaches and show their performance with real (able-bodied) participants (with restricted motion). This project will not only advance the state of the art in assistive robotics, robot learning and human-safe control, but also will play a major role in helping persons with reduced mobility to live independently for longer and with a better quality of life. Campo scientifico engineering and technologymaterials engineeringtextilesengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics Parole chiave Robot learning robotic assistant programming by demonstration human-robot interaction physical human-robot interaction reinforcement learning Interactive Learning Deformable objects Programma(i) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Argomento(i) MSCA-IF-2016 - Individual Fellowships Invito a presentare proposte H2020-MSCA-IF-2016 Vedi altri progetti per questo bando Meccanismo di finanziamento MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinatore AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS Contribution nette de l'UE € 170 121,60 Indirizzo CALLE SERRANO 117 28006 Madrid Spagna Mostra sulla mappa Regione Comunidad de Madrid Comunidad de Madrid Madrid Tipo di attività Research Organisations Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 170 121,60