Human-in-the-Loop Approach to Safe Navigation of a Smart Wheelchair via Brain Computer Interface

Assistive robots operate in complex environments and in presence of human beings, as such they are influenced by several factors which may lead to undesired outcomes: wrong sensor readings, unexpected environmental conditions or algorithmic errors represent just few examples. When the safety of the user must be guaranteed, a possible solution is to rely on a human-in-the-loop approach, e.g. to monitor if the robot performs a wrong action or environmental conditions affect safety during the interaction, and provide a feedback accordingly. The proposed work presents a human supervised smart wheelchair, i.e. an electric powered wheelchair with semiautonomous navigation capabilities of elaborating a path planning, whose user is equipped with a Brain Computer Interface (BCI) to provide safety feedbacks. During the wheelchair navigation towards a desired destination in an indoor scenario, possible problems (e.g. obstacles) along the trajectory cause the generation of error-related potentials signals (ErrPs) when noticed by the user. These signals are captured by the interface and are used to provide a feedback to the navigation task, in order to preserve safety and avoiding possible navigation issues modifying the trajectory planning.