Abstract
Robots have garnered significant attention owing to their advantages in terms of replacing human labor under hazardous environments. In particular, because underwater construction robots can perform various tasks that are highly dangerous under deep sea environments, the development of manipulator control technology for these underwater robots is crucial. In this study, we therefore introduce an underwater manipulator control method based on meta reinforcement learning. Specifically, we construct a real-world underwater robot manipulator environment using ROS Gazebo and conduct simulations for the testing and verification of the proposed method.
| Original language | English |
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| Title of host publication | 2021 21st International Conference on Control, Automation and Systems (ICCAS) |
| Place of Publication | Piscataway, N.J. |
| Publisher | IEEE |
| Pages | 1473-1476 |
| Number of pages | 4 |
| ISBN (Electronic) | 9788993215212 |
| ISBN (Print) | 9781665418324 |
| DOIs | |
| Publication status | Published - 28 Dec 2021 |
| Event | 21st International Conference on Control, Automation and Systems, ICCAS 2021 - Jeju, Korea, Republic of Duration: 12 Oct 2021 → 15 Oct 2021 |
Publication series
| Name | International Conference on Control, Automation and Systems |
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| Volume | 2021-October |
| ISSN (Print) | 1598-7833 |
Conference
| Conference | 21st International Conference on Control, Automation and Systems, ICCAS 2021 |
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| Country/Territory | Korea, Republic of |
| City | Jeju |
| Period | 12/10/21 → 15/10/21 |
Funding
This research was supported by the MISP(Ministry of Science, ICT & Future Planning), Korea, under the National Program for Excellence in SW(2017-0-00137) supervised by the IITP(Institute of Information & communications Technology Planning & Evaluation) (2017-0-00137)
Keywords
- manipulator control
- meta reinforcement learning
- model based reinforcement learning
- robotic manipulation
- underwater robot