Stable Estimator of Dynamical Systems
Stable Estimator of Dynamical Systems (SEDS) is powerful method to
tackle the big challenge in using Dynamical Systems. SEDS learns the
parameters of the DS to ensure that all motions follow closely the
demonstrations while ultimately reaching in and stopping at the target.
More precisely, SEDS is a constrained optimization algorithm that
formulates any arbitrary motion as a Mixture of Gaussian Functions. The
objective function of SEDS could be mean square error or likelihood.
The constraints in SEDS guarantees the global asymptotic stability of a
non-linear time-independent DS.
More information on the IROS 2010 paper.