31 research outputs found
Personalization framework for adaptive robotic feeding assistance
The final publication is available at link.springer.comThe deployment of robots at home must involve robots with pre-defined skills and the capability of
personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied
to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using
Learning-by- Demostration, and a ProMP formalism to compute an overall trajectory and the variance along the path.
Experiments show the validity of the approach in generating different feeding motions to adapt to user’s preferences,
automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also
assessed, and two training strategies are compared. © Springer International Publishing AG 2016.Peer ReviewedPostprint (author's final draft