7 citations · 28 across the 8 of their papers we have counts for
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cs.RO2022
Learning robot inverse dynamics using sparse online Gaussian process with forgetting mechanism
Wei Li, Zhiwen Li, Yiqi Liu +1
Online Gaussian processes (GPs), typically used for learning models from time-series data, are more flexible and robust than offline GPs. Both local and sparse approximations of GP…
cs.LG2022★ 7 cited
Composite FORCE learning of chaotic echo state networks for time-series prediction
Yansong Li, Kai Hu, Kohei Nakajima +1
Echo state network (ESN), a kind of recurrent neural networks, consists of a fixed reservoir in which neurons are connected randomly and recursively and obtains the desired output…
cs.RO2022★ 7 cited
Bioinspired composite learning control under discontinuous friction for industrial robots
Yongping Pan, Kai Guo, Tairen Sun +1
Adaptive control can be applied to robotic systems with parameter uncertainties, but improving its performance is usually difficult, especially under discontinuous friction. Inspir…