Abstract: Impedance control is one of the most effective control methods for the manipulators in contact with their environments.
The present paper proposes a new method to regulate the impedance parameter of the end-effector through learning of neural networks. Three kinds of the feed- ...
Abstruct-lmpedance control is one of the most effective control methods for the manipulators in contact with their environments.
Impedance control is one of the most effective control methods for the manipulators in contact with their environments. The characteristics of force and ...
The present paper proposesa new method to regulate the impedance parameter of theend-effector through learning of neural networks. Three kindsof the feed- ...
This report presents a method that uses neural networks to regulate impedance parameters of the manipulator's end-effector while identifying environmental ...
In this paper, a neural-network-based framework for learning variable impedance skills is proposed. The proposed approach builds the full stiffness function.
Missing: operational | Show results with:operational
Aug 27, 2019 · In this paper, we focus on a physical training scenario, where the robot needs to adjust its impedance parameters according to the human user's performance.
May 16, 2023 · The simulation results show that the designed neural network impedance control strategy can achieve a control accuracy of less than 10 − 3 rad ...
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This paper proposes a simultaneous learning method to regulate the impedance parameters using neural networks. The validity of the proposed method is ...