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Leopoldo Armesto

2 accepted papers

2017

Efficient learning of constraints and generic null space policies

ICRA 2017poster

A large class of motions can be decomposed into a movement task and null-space policy subject to a set of constraints. When learning such motions from demonstrations, we aim to achieve generalisation across different unseen constraints and to increase the robustness to noise while keeping the comput…

Cited by 32SourceScholar
2017

Learning Constrained Generalizable Policies by Demonstration

RSS 2017poster

Many practical tasks in robotic systems, such as cleaning windows, writing or grasping, are inherently constrained. Learning policies subject to constraints is a challenging problem. We propose a \emph{locally weighted constrained projection learning} method (LWCPL) that first estimates the constra…

Cited by 14SourcePDFScholar