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.