|Name||Developmental Learning of Internal Models for Robotic Manipulation based on Motor Primitives and Multisensory Integration|
|Funding Reference||FP7-PEOPLE-IEF- 628315|
Dexterous manipulation is a key challenge for the dissemination of robots in our society: most of the tasks robots can be useful for resort in some form of manipulation of objects. However, unlike humans, robots only achieve good performances in very controlled settings, failing to scale to unknown environments or novel objects. This project focuses on three main aspects of human motor control that can be combined to improve the performances of current robots: internal models, development and multisensory integration.
Computer and Robot Vision Lab (VisLab)
Developmental Learning of Internal Models for Robotic Manipulation based on Motor Primitives and Multisensory Integration