Learning from Demonstrations with Koopman Operators for Robotics
We learn dynamical systems from demonstrations for robot motion planning with the Koopman operator.
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We learn dynamical systems from demonstrations for robot motion planning with the Koopman operator.
We present EnKode, an active learning framework based on Koopman operator theory for modeling unknown flow fields and guiding robotic active sensing with uncertainty quantification
We develop a learning framework for online modeling of the global dynamics of complex dynamical systems using Koopman operator theory and Fourier Features.