A closed-loop brain-computer interface with augmented reality feedback for industrial human-robot collaboration

Industrial human-robot collaboration (HRC) aims to combine human intelligence and robotic capability to achieve higher productiveness. In industrial HRC, the communication between humans and robots is essential to enhance the understanding of the intent of each other to make a more fluent collaboration. Brain-computer interface (BCI) is a technology that could record the user’s brain activity that can be translated into interaction messages (e.g., control commands) to the outside world, which can build a direct and efficient communication channel between human and robot. However, due to lacking information feedback mechanisms, it is challenging for BCI to control robots with a high degree of freedom with a limited number of classifiable mental states. To address this problem, this paper proposes a closed-loop BCI with contextual visual feedback by an augmented reality (AR) headset. In such BCI, the electroencephalogram (EEG) patterns from the multiple voluntary eye blinks are considered the input and its online detection algorithm is proposed whose average accuracy can reach 94.31%. Moreover, an AR-enable information feedback interface is designed to achieve an interactive robotic path planning. A case study of an industrial HRC assembly task is also developed to show that the proposed closed-up BCI could shorten the time of user input in human-robot interaction.