Enhancing robot behavior with EEG, reinforcement learning and beyond: a review of techniques in collaborative robotics
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2024-07-20
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Multidisciplinary Digital Publishing Institute (MDPI)
Resumen
Collaborative robotics is a major topic in current robotics research, posing new challenges, especially in human–robot interaction. The main aspect in this area of research focuses on understanding the behavior of robots when engaging with humans, where reinforcement learning is a key discipline that allows us to explore sophisticated emerging reactions. This review aims to delve into the relevance of different sensors and techniques, with special attention to EEG (electroencephalography data on brain activity) and its influence on the behavior of robots interacting with humans. In addition, mechanisms available to mitigate potential risks during the experimentation process such as virtual reality are also be addressed. In the final part of the paper, future lines of research combining the areas of collaborative robotics, reinforcement learning, virtual reality, and human factors are explored, as this last aspect is vital to ensuring safe and effective human–robot interactions.
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Applied artificial intelligence
Human–robot collaboration
Human–robot interaction
Robotics
Applied artificial intelligence
Human–robot collaboration
Human–robot interaction
Robotics
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Gonzalez-Santocildes, A., Vazquez, J.-I., & Eguiluz, A. (2024). Enhancing robot behavior with EEG, reinforcement learning and beyond: a review of techniques in collaborative robotics [Review of enhancing robot behavior with EEG, reinforcement learning and beyond: a review of techniques in collaborative robotics]. Applied Sciences (Switzerland), 14(14). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/APP14146345