Robots and the sense of Touch
Humans make extensive use of touch. However, integrating the sense of touch in robot control has traditionally proved to be a difficult task. In this talk, I will discuss how machine learning can help to provide robots with the sense of touch, and the benefits of doing so.
Roberto Calandra is a Research Scientist at Facebook AI Research (FAIR). Previously, he was a postdoctoral scholar at UC Berkeley in the Berkeley Artificial Intelligence Research Laboratory (BAIR) working with Sergey Levine. Roberto received a Ph.D. from TU Darmstadt (Germany) under the supervision of Jan Peters and Marc Deisenroth, a M.Sc. in Machine Learning and Data Mining from the Aalto university (Finland), and a B.Sc. in Computer Science from the Università degli studi di Palermo (Italy). His scientific interests focus at the conjunction of Machine Learning and Robotics, in what is know as Robot Learning.