Robot learning from few demonstrations by exploiting the structure and geometry of data
EPFL – École Polytechnique Fédérale de Lausanne –
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).
Dr Sylvain Calinon is a Senior Researcher at the Idiap Research Institute (http://idiap.ch). He is also a lecturer at the Ecole Polytechnique Federale de Lausanne (EPFL), and an external collaborator at the Department of Advanced Robotics (ADVR), Italian Institute of Technology (IIT). From 2009 to 2014, he was a Team Leader at ADVR, IIT. From 2007 to 2009, he was a Postdoc at the Learning Algorithms and Systems Laboratory, EPFL, where he obtained his PhD in 2007. He is the author of 100+ publications at the crossroad of robot learning, adaptive control and human-robot interaction, with recognition including Best Paper Awards in the journal of Intelligent Service Robotics (2017) and at IEEE Ro-Man’2007, as well as Best Paper Award Finalist at ICRA’2016, ICIRA’2015, IROS’2013 and Humanoids’2009. He currently serves as Associate Editor in IEEE Transactions on Robotics (T-RO), IEEE Robotics and Automation Letters (RA-L), Intelligent Service Robotics (Springer), and Frontiers in Robotics and AI.
Personal website: http://calinon.ch
Date: 2018-Jun-06 Time: 11:00:00 Room: IST Alameda – DEI Informática II, room 0.19
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Workshop “Metabolism and mathematical models: Two for a tango” – 2nd Edition
Title: Workshop Metabolism and mathematical models: Two for a tango – 2nd Edition
Dates: October 25-26, 2022
Location: This workshop will be held in a virtual way
The topic of this workshop is metabolism in general, with a special focus, although not exclusive, on parasitology. Besides an exploration of the biological, biochemical and biomedical aspects, the workshop will also aim at presenting some of the mathematical modelling, algorithmic theory and software development that have become crucial to explore such aspects.
This workshop is being organised in the context of two projects, both with the Inria European Team Erable. One of the projects involves a partnership with the University of São Paulo (USP), in São Paulo, Brazil, more specifically the Institute of Mathematics and Statistics (IME) and the Institute of Biomedical Sciences – Inria Associated Team Capoeira – and the other involves the Inesc-ID/IST in Portugal, ETH in Zürich and EMBL in Heidelberg – H2020 Twinning Project Olissipo.
The workshop is open to all members of these two projects but also, importantly, to the community in general.
The program and more details are available here.