Learning Assembly Tasks in a Few Minutes by Combining Impedance Control and Residual Recurrent Reinforcement Learning-Reference-Cited by-同舟云学术

Learning Assembly Tasks in a Few Minutes by Combining Impedance Control and Residual Recurrent Reinforcement Learning

Published:2021-09-02 Issue:1 Volume:4 Page:2100095
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Kulkarni Padmaja¹,Kober Jens¹,Babuška Robert¹²,Della Santina Cosimo¹³^ORCID

Affiliation:

1. Department of Cognitive Robotics Delft University of Technology Delft 2628 CD The Netherlands

2. Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 160 00 Czech Republic

3. Institute of Robotics and Mechatronics German Aerospace Center (DLR) Oberpfaffenhofen 82234 Germany

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202100095

Reference45 articles.

1. P.Zou Q.Zhu J.Wu J.Jin inProc. – 2019 Chinese Automation Congress CAC 2019 IEEE Piscataway NJ2019 pp.3269–3273.

2. A.Bicchi V.Kumar inProc. 2000 ICRA. Millennium Conf. IEEE Int. Conf. on Robotics and Automation. Symp. Proc.(Cat. No.00CH37065) IEEE Piscataway NJ2020 p.1.

3. Trends and challenges in robot manipulation

4. L.Manuelli W.Gao P.Florence R.Tedrake kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation arXiv 2019.

5. H.Bruyninckyx S.Dutre J.De Schutter inProc. – IEEE Int. Conf. on Robotics and Automation vol.2 IEEE Piscataway NJ1995 pp.1919–1924.

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning vision-based robotic manipulation tasks sequentially in offline reinforcement learning settings;Robotica;2024-05-02

2. Task attention-based multimodal fusion and curriculum residual learning for context generalization in robotic assembly;Applied Intelligence;2024-03

3. Physics‐Informed Neural Networks to Model and Control Robots: A Theoretical and Experimental Investigation;Advanced Intelligent Systems;2024-02-23

4. A residual reinforcement learning method for robotic assembly using visual and force information;Journal of Manufacturing Systems;2024-02

5. Deep Imitation Learning for Optimal Trajectory Planning and Initial Condition Optimization for an Unstable Dynamic System;Advanced Intelligent Systems;2023-11-27