Representing movement primitives as implicit dynamical systems learned from multiple demonstrations
2013 (English)In: Proceedings of the International Conference on Advanced Robotics (ICAR), IEEE , 2013, 1-8 p.Conference paper (Refereed)
This work deals with the problem of parameter estimation of dynamical systems intended to model demonstrated motion profiles for a system of interest. The regression problem is formulated as a constrained nonlinear least squares problem. We present an approach that extends the concept of dynamical movement primitives to account for multiple demonstrations of a motion. We maintain an implicit dynamical system that resembles the demonstrated trajectories in a locally optimal way. This is achieved by solving a quadratic program (that encodes our notion of resemblance) at each sampling time step. Our method guarantees predictable state evolution even in regions of the state space not covered by the demonstrations.
Place, publisher, year, edition, pages
IEEE , 2013. 1-8 p.
Robotics, Motion Control, Motion Planning, Embedded Optimization
Research subject Computer Science
IdentifiersURN: urn:nbn:se:oru:diva-33427DOI: 10.1109/ICAR.2013.6766505ScopusID: 2-s2.0-84899426598OAI: oai:DiVA.org:oru-33427DiVA: diva2:691954
International Conference on Advanced Robotics (ICAR),Nov 25 - Nov 29, Montevideo, Uruguay
ProjectsEU-FP7 HANDLEEU-FP7 ROBLOG
FunderEU, FP7, Seventh Framework Programme, J44528EU, FP7, Seventh Framework Programme, J44520