A Novel Multimodal Humanoid Robot Control System Framework Design Based on SSVEP-BCI and Eye-Tracking

Abstract:
As population ageing increases, Brain-Computer Interface (BCI) technology combined with humanoid robots has become an innovative solution to alleviate the stress of elderly care. To improve the reliability and stability of the BCI system in practical applications, this paper proposed a novel multimodal humanoid robot control system. There are two different control modalities in parallel: Steady State Visual Evoked Potential (SSVEP)-BCI control modality and Eye Tracking control modality. The system utilized blinks events enable the user to initiate the human-machine interface (HMI) autonomously, selected one of the control modes based on the user's attention state, and sent control commands to the robot for execution. This multimodal framework effectively solves the false triggering problem of the humanoid BCI system, and the humanoid robot can perform tasks more flexibly.