Bridge laboratory BCI paradigms and embodied, fluid robotic interaction

Develop EEG-based brain–computer interface control approaches that enable seamless, continuous, and intuitive interaction with mobile robots such as assistive robotic wheelchairs, thereby bridging the gap between laboratory-designed discrete BCI paradigms (including spontaneous motor imagery and evoked responses) and the embodied, fluid robotic control required for real-world navigation.

Background

The paper reviews that most EEG-based BCI systems have been designed around discrete, low-dimensional tasks (e.g., selection commands), which do not naturally translate to continuous, embodied control needed for mobile robots in real environments.

The authors argue that achieving smooth, flexible, real-time control remains difficult due to the non-stationarity of EEG signals and the mismatch between traditional BCI paradigms and the demands of continuous robotic navigation. This motivates the need for methods that close this gap to enable embodied, fluid interaction.