Abstract: Due to the excessive degree of freedom of the space flexible manipulator, we can hardly obtain its accurate dynamic model for its motion planning.
Dec 1, 2019 · Firstly, we use the RND method to jointly train a predictive network and a fixed network. The discrepancy between the output values of the two ...
... We use the soft actor-critic (SAC) algorithm [29] with the double Qlearning scheme due to its sample efficiency and stability concerning hyperparameter ...
Abstract – Due to the excessive degree of freedom of the space flexible manipulator, we can hardly obtain its accurate dynamic model for its motion planning ...
Due to the excessive degree of freedom of the space flexible manipulator, we can hardly obtain its accurate dynamic model for its motion planning.
Trajectory tracking control based on deep reinforcement learning and ...
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A deep RL(DRL) approach combining the soft actor-critic (SAC) algorithm and ensemble random network distillation (ERND) is proposed to address the tracking ...
Jul 19, 2024 · This paper presents a model-based reinforcement learning framework for precise control of FFSMs with dynamics unknown.
This work uses soft Q-learning (SQL) algorithm to train stochastic energy based policies for space manipulator motion planning and trains policies that ...
Oct 18, 2024 · A deep RL(DRL) approach combining the soft actor-critic (SAC) algorithm and ensemble random network distillation (ERND) is proposed to address ...
Sep 1, 2022 · In this study, we examined the advantages of a continuum robot arm as compared to a typical and rigid seven-degree-of-freedom (7-DoF) robot manipulator.