Sujuan Wei

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Imitation learning is a promising paradigm for enabling robots to autonomously perform new tasks, which is similar to the procedure of human's motion skill acquirement. In the paper, we present a novel DS-GMR coupled primitive (DGCP) for robotic motion skill learning based on imitation learning. DGCP comprises a dominated linear ordinary differential(More)
Dynamic movement primitives (DMPs) is very powerful model to conduct learning from demonstration for robot. In this paper, we put forward a method for forcing term learning based on Gaussian Model Regression (GMR). Specifically, we apply the Gaussian Mixture Model (GMM) to model the jointly probability over data from demonstrations (desired values,(More)
We present a novel online learning control algorithm (OLCPA) which comprises projected gradient temporal difference for action-value function (PGTDAVF) and advanced heuristic dynamic programming with one step delay (AHD-POSD). PGTDAVF can guarantee the convergence of temporal difference(TD)-based policy learning with smooth action-value function(More)
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