IEEE Access (Jan 2020)

A Systematic Review on Reinforcement Learning-Based Robotics Within the Last Decade

  • Md. Al-Masrur Khan,
  • Md Rashed Jaowad Khan,
  • Abul Tooshil,
  • Niloy Sikder,
  • M. A. Parvez Mahmud,
  • Abbas Z. Kouzani,
  • Abdullah-Al Nahid

DOI
https://doi.org/10.1109/ACCESS.2020.3027152
Journal volume & issue
Vol. 8
pp. 176598 – 176623

Abstract

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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.

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