Closed-Loop Dynamic Control of a Soft Manipulator Using Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Closed-Loop Dynamic Control of a Soft Manipulator Using Deep Reinforcement Learning

Published:2022-04 Issue:2 Volume:7 Page:4741-4748
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Centurelli Andrea¹,Arleo Luca¹^ORCID,Rizzo Alessandro²^ORCID,Tolu Silvia³^ORCID,Laschi Cecilia⁴^ORCID,Falotico Egidio¹^ORCID

Affiliation:

1. BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera, Italy

2. Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy

3. Department of Electrical Engineering (Automation and Control), Technical University of Denmark, Lyngby, Denmark

4. Department of Mechanical Engineering, National University of Singapore, Singapore

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/9647862/09697385.pdf?arnumber=9697385

Reference27 articles.

1. Learning Closed Loop Kinematic Controllers for Continuum Manipulators in Unstructured Environments

2. Data-Driven Control of Soft Robots Using Koopman Operator Theory

3. Using First Principles for Deep Learning and Model-Based Control of Soft Robots

4. Control Strategies for Soft Robotic Manipulators: A Survey

5. Open Loop Position Control of Soft Continuum Arm Using Deep Reinforcement Learning

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