4 Junho 2018, 10:42 - Luís Revez
You are cordially invited to attend the seminar “ROBOT LEARNING FROM FEW DEMONSTRATIONS BY EXPLOITING THE STRUCTURE AND GEOMETRY OF DATA”, which is scheduled on Wednesday June 6th, 11:00 AM at Informática II, room 0.17, Alameda
The invited speaker for this seminar is DR. SYLVAIN CALINON, a permanent Senior Researcher at IDIAP Research Institute, Switzerland.
Please find below the abstract of the talk and the biography of Dr. Calinon.
Title: Robot learning from few demonstrations by exploiting the structure and geometry of data
Abstract: Many human-centered robot applications would benefit from the development of robots that could acquire new movements and skills from human demonstration, and that could reproduce these movements in new situations. From a machine learning perspective, the challenge is to acquire skills from only few interactions with strong generalization demands. It requires the development of intuitive active learning interfaces to acquire meaningful demonstrations, the development of models that can exploit the structure and geometry of the acquired data in an efficient way, and the development of adaptive controllers that can exploit the learned task variations and coordination patterns. The developed models need to serve several purposes (recognition, prediction, generation), and be compatible with different learning strategies (imitation, emulation, exploration).
I will present an approach combining model predictive control, statistical learning and differential geometry to pursue such goal. I will illustrate the proposed approach with various applications, including robots that are close to us (human-robot collaboration, robot for dressing assistance), part of us (prosthetic hand control from tactile array data), or far from us (teleoperation of bimanual robot in deep water).