An Assistive Shared Control Architecture for a Robotic Arm Using EEG-Based BCI with Motor Imagery

Abstract

The paper presents a shared control architecture for robotic systems commanded through a motor imagery based Brain-Computer Interface (BCI). The overall system is aimed at assisting people to perform teleoperated manipulation tasks, and it is structured so as to leave different levels of autonomy to the user depending on the actual stage of the task execution. The low-level part of the shared control architecture is also in charge of taking into account safety and operational tasks, such as to avoid collisions or to manage robot joint limits. The overall architecture has been realized by integrating control and perception software modules developed within the ROS environment, with the OpenVibe framework used to operate the BCI device. The effectiveness of the proposed architecture has been validated through experiments where a healthy user, wearing a Unicorn g.tec BCI, performs an assisted task through motor imagery sessions, with a 7 Degrees of Freedoms Kinova Jaco2 robotic arm.