Tumbling Robot Control Using Reinforcement Learning: An Adaptive Control Policy That Transfers Well to the Real World-Reference-Cited by-同舟云学术

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Tumbling Robot Control Using Reinforcement Learning: An Adaptive Control Policy That Transfers Well to the Real World

Published:2022 Issue: Volume: Page:2-11
ISSN:1070-9932
Container-title:IEEE Robotics & Automation Magazine
language:
Short-container-title:IEEE Robot. Automat. Mag.

Author:

Schwartzwald Andrew¹,Tlachac Matthew²,Guzman Luis³,Bacharis Thanasis⁴,Papanikolopoulos Nikos⁵^ORCID

Affiliation:

1. CSE, CSE, UMN, Sun Prairie, WI 53590 United States of America

2. MnRI, CSE, UMN, Minneapolis, MN 55414 United States of America

3. CSE, University of Minnesota, United States of America

4. Computer Science, CSE, UMN, Rochester, Minnesota 55906 United States of America

5. Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455 United States of America

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/100/4600619/09845375.pdf?arnumber=9845375

Cited by 2 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. Reward Design for Training Robotic Insertion Tasks Using Low-Dimensional Observation;Proceedings of the 2024 4th International Conference on Robotics and Control Engineering;2024-06-27

2. Petri Net Modelling and Motion Analysis of the Football Robot System;2023 China Automation Congress (CAC);2023-11-17

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