Gonzalez-Santocildes, A.; Vazquez, J.-I.; Eguiluz, A. Enhancing Robot Behavior with EEG, Reinforcement Learning and Beyond: A Review of Techniques in Collaborative Robotics. Applied Sciences 2024, 14, 6345, doi:10.3390/app14146345.
Gonzalez-Santocildes, A.; Vazquez, J.-I.; Eguiluz, A. Enhancing Robot Behavior with EEG, Reinforcement Learning and Beyond: A Review of Techniques in Collaborative Robotics. Applied Sciences 2024, 14, 6345, doi:10.3390/app14146345.
Gonzalez-Santocildes, A.; Vazquez, J.-I.; Eguiluz, A. Enhancing Robot Behavior with EEG, Reinforcement Learning and Beyond: A Review of Techniques in Collaborative Robotics. Applied Sciences 2024, 14, 6345, doi:10.3390/app14146345.
Gonzalez-Santocildes, A.; Vazquez, J.-I.; Eguiluz, A. Enhancing Robot Behavior with EEG, Reinforcement Learning and Beyond: A Review of Techniques in Collaborative Robotics. Applied Sciences 2024, 14, 6345, doi:10.3390/app14146345.
Abstract
Collaborative robotics is a major topic in current robotics research posing new challenges, especially in Human-Robot Interaction. The crucial 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 will 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 will be explored, as this last aspect is vital to ensure safe and effective Human-Robot Interactions.
Copyright:
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