Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model

no code implementations • TRANSACTION 2020 • Yazhou Hu, Wenxue Wang, Hao liu, and Lianqing Liu, Member, IEEE

In this algorithm, a reward function is defined according to the features of tracking control in order to speed up the learning process, and then an RL tracking controller with a kernel-based transition dynamic model is proposed.

Continuous Control reinforcement-learning +1

Robotic Tracking Control with Kernel Trick-based Reinforcement Learning

no code implementations • Conference 2019 • Yazhou Hu, 1 Wenxue Wang† 2, Hao Liu3 and Lianqing Liu 2

And then, a kernel trick-based reinforcement learning tracking controller is presented to perform tracking control tasks on a robotic manipulator system.

reinforcement-learning Reinforcement Learning (RL)

A Reinforcement Learning Neural Network for Robotic Manipulator Control

no code implementations • Conference 2018 • Yazhou Hu, Bailu Si

The three networks work together to optimize the performance index based on the reinforcement learning control scheme.

reinforcement-learning Reinforcement Learning (RL)