JOÃO SILVÉRIO

Robotics Researcher

Advanced Robotics Department
Italian Institute of Technology

My goal is to create new algorithms that allow robots to learn complex motor skills from humans. I tend to exploit probabilistic machine learning techniques in combination with classical robotics concepts, (optimal) control and, recently, some reinforcement learning. I usually experiment with uni- and bi-manual manipulation applications as well as physical collaboration/interaction with humans.

Check the Publications section to learn more about my work!

Google Scholar

News & Updates

[New] 23/3/2019 - Co-authored paper Kernelized Movement Primitives accepted for publication at IJRR! This work addresses motor skill learning by imitation, with a particular focus on generalization and multi-dimensional inputs.
8/10/2018 - Great news! Our paper on learning task priorities from demonstrations has been accepted at the IEEE Transactions on Robotics! Check the Publications section for details.
19/9/2018 - One paper accepted at Humanoids'18!
30/6/2018 - Three papers accepted at IROS'18! Check Publications section for details.
15/1/2018 - Good news! Our two submissions have been accepted at ICRA'18!
29/8/2017 - New co-authored arXiv pre-print "Kernelized Movement Primitives" available in Publications.
21/7/2017 - New pre-print "Learning Competing Constraints and Task Priorities from Demonstrations of Bimanual Skills" (under review at IEEE Transactions on Robotics) available.
6/7/2017 - The co-authored arXiv pre-print "Generalized Task-Parameterized Movement Primitives" (currently under review for publication at ICRA'18) is now available in Publications.
19/4/2017 - I successfully defended my PhD Thesis at IIT! Sincere thanks to everyone who made it possible, especially to Sylvain Calinon, Leonel Rozo and Darwin Caldwell.