Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems
Authors:
- Nicolas PerrinNPNicolas Perrin
- Philipp Schlehuber-CaissierPSPhilipp Schlehuber-Caissier
- 1 October 2016
- journal article
- research article
- Published by Elsevier in Systems & Control Letters
- Vol. 96, 51-59
Abstract
No abstract availableKeywords
Funding Information
- European Union’s Horizon 2020 Research and Innovation Programme (640891)
This publication has 11 references indexed in Scilit:
- Learning robot motions with stable dynamical systems under diffeomorphic transformationsRobotics and Autonomous Systems, 2015
- Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motionsRobotics and Autonomous Systems, 2014
- Neural learning of stable dynamical systems based on data-driven Lyapunov candidates2013
- Dynamical Movement Primitives: Learning Attractor Models for Motor BehaviorsNeural Computation, 2013
- Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture ModelsIEEE Transactions on Robotics, 2011
- Large Deformation Diffeomorphic Metric Curve MappingInternational Journal of Computer Vision, 2008
- Computational approaches to motor learning by imitationPhilosophical Transactions of the Royal Society B: Biological Sciences, 2003
- Landmark matching via large deformation diffeomorphismsIEEE Transactions on Image Processing, 2000
- Variational problems on flows of diffeomorphisms for image matchingQuarterly of Applied Mathematics, 1998
- The construction of analytic diffeomorphisms for exact robot navigation on star worldsTransactions of the American Mathematical Society, 1991