  In this study, we propose a shared control method for teleoperated mobile
robots using brain-machine interfaces (BMI). The control commands generated
through BMI for robot operation face issues of low input frequency,
discreteness, and uncertainty due to noise. To address these challenges, our
method estimates the user's intended goal from their commands and uses this
goal to generate auxiliary commands through the autonomous system that are both
at a higher input frequency and more continuous. Furthermore, by defining the
confidence level of the estimation, we adaptively calculated the weights for
combining user and autonomous commands, thus achieving shared control.
