Real-Robot Deep Reinforcement Learning: Improving Trajectory Tracking of Flexible-Joint Manipulator with Reference Correction
Author:
Affiliation:
1. University of Bonn,Autonomous Intelligent Systems (AIS) Group, Computer Science Institute VI,Germany
Funder
German Research Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9811522/9811357/09812023.pdf?arnumber=9812023
Reference33 articles.
1. Flexible-Joint Manipulator Trajectory Tracking with Learned Two-Stage Model employing One-Step Future Prediction
2. Comparison of linearized dynamic robot manipulator models for model predictive control
3. Comparing Model Predictive Control and input shaping for improved response of low-impedance robots
4. Revisiting fundamentals of experience replay;fedus;International Conference on Machine Learning (ICML),0
5. A survey of iterative learning control
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