A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade
Robotics is one of the many tools that is making a substantial difference as the world is experiencing the fourth industrial revolution. To ease control over this engineering marvel substantially, Reinforcement Learning (RL) has paved its way in recent years quite remarkably. RL enables robots to be...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9206554/ |
| _version_ | 1818662494031314944 |
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| author | Md. Al-Masrur Khan Md Rashed Jaowad Khan Abul Tooshil Niloy Sikder M. A. Parvez Mahmud Abbas Z. Kouzani Abdullah-Al Nahid |
| author_facet | Md. Al-Masrur Khan Md Rashed Jaowad Khan Abul Tooshil Niloy Sikder M. A. Parvez Mahmud Abbas Z. Kouzani Abdullah-Al Nahid |
| author_sort | Md. Al-Masrur Khan |
| collection | DOAJ |
| description | Robotics is one of the many tools that is making a substantial difference as the world is experiencing the fourth industrial revolution. To ease control over this engineering marvel substantially, Reinforcement Learning (RL) has paved its way in recent years quite remarkably. RL enables robots to become self-aware towards carrying out a specific task followed by user operations. For decades of rigorous endeavor, this research field has gone through numerous groundbreaking developments and it will be the same for the coming days. Therefore, this paper steps in to enlighten the scientific community with a systemic review of the published research papers within the past decade. The bibliographic data that is extracted from the papers are analyzed using an automated tool named Vosviewer with respect to some parameters. Substantial excerpts from the most influential papers are highlighted in this work. Furthermore, this paper points out the global research practice in this field. The paper also generates some intriguing questions and answers them in regards to the research topic. After reading this paper, future researchers will have a firm idea in the RL-based robotics and will be able to incorporate in their own research. |
| first_indexed | 2024-12-17T05:01:50Z |
| format | Article |
| id | doaj.art-4e6679cd36b942e2b000af469780c9b9 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T05:01:50Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-4e6679cd36b942e2b000af469780c9b92022-12-21T22:02:32ZengIEEEIEEE Access2169-35362020-01-01817659817662310.1109/ACCESS.2020.30271529206554A Systematic Review on Reinforcement Learning-Based Robotics Within the Last DecadeMd. Al-Masrur Khan0https://orcid.org/0000-0002-1729-4071Md Rashed Jaowad Khan1Abul Tooshil2Niloy Sikder3https://orcid.org/0000-0002-9016-6105M. A. Parvez Mahmud4https://orcid.org/0000-0002-1905-6800Abbas Z. Kouzani5https://orcid.org/0000-0002-6292-1214Abdullah-Al Nahid6https://orcid.org/0000-0003-2391-5767Electronics and Communication Engineering Discipline, Khulna University, Khulna, BangladeshElectronics and Communication Engineering Discipline, Khulna University, Khulna, BangladeshElectronics and Communication Engineering Discipline, Khulna University, Khulna, BangladeshComputer Science and Engineering Discipline, Khulna University, Khulna, BangladeshSchool of Engineering, Deakin University, Geelong, VIC, AustraliaSchool of Engineering, Deakin University, Geelong, VIC, AustraliaElectronics and Communication Engineering Discipline, Khulna University, Khulna, BangladeshRobotics is one of the many tools that is making a substantial difference as the world is experiencing the fourth industrial revolution. To ease control over this engineering marvel substantially, Reinforcement Learning (RL) has paved its way in recent years quite remarkably. RL enables robots to become self-aware towards carrying out a specific task followed by user operations. For decades of rigorous endeavor, this research field has gone through numerous groundbreaking developments and it will be the same for the coming days. Therefore, this paper steps in to enlighten the scientific community with a systemic review of the published research papers within the past decade. The bibliographic data that is extracted from the papers are analyzed using an automated tool named Vosviewer with respect to some parameters. Substantial excerpts from the most influential papers are highlighted in this work. Furthermore, this paper points out the global research practice in this field. The paper also generates some intriguing questions and answers them in regards to the research topic. After reading this paper, future researchers will have a firm idea in the RL-based robotics and will be able to incorporate in their own research.https://ieeexplore.ieee.org/document/9206554/Bibliometric analysisreinforcement learningroboticssystematic review |
| spellingShingle | Md. Al-Masrur Khan Md Rashed Jaowad Khan Abul Tooshil Niloy Sikder M. A. Parvez Mahmud Abbas Z. Kouzani Abdullah-Al Nahid A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade IEEE Access Bibliometric analysis reinforcement learning robotics systematic review |
| title | A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade |
| title_full | A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade |
| title_fullStr | A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade |
| title_full_unstemmed | A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade |
| title_short | A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade |
| title_sort | systematic review on reinforcement learning based robotics within the last decade |
| topic | Bibliometric analysis reinforcement learning robotics systematic review |
| url | https://ieeexplore.ieee.org/document/9206554/ |
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