Human-machine shared control method for brain-controlled wheeled robot

Human-machine shared control has been verified to be an effective method for brain-controlled robot. This paper proposes a shared control system for wheeled robots, which converts the EEG signals generated by SSVEP into the BCI command of the wheeled robot through vector fusion, and designs the RAC method to adjust the human-machine control weight based on the confidence evaluation of the EEG signals and the robot environment evaluation. Considering the problem of human-machine conflict, this paper adopts a "people-oriented" strategy and proposes the SCR-TEB algorithm to resolve human-machine conflicts. Online experiments have proved that the method proposed in this paper can effectively improve the success rate of the task and give people a stronger sense of control.