TY - JOUR
AU1 - Li, Mengfan
AU2 - Wei, Ran
AU3 - Zhang, Ziqi
AU4 - Zhang, Pengfei
AU5 - Xu, Guizhi
AU6 - Liao, Wenzhe
AB - Brain–computer interface (BCI) is a typical direction of integration of human intelligence and robot intelligence. Shared control is an essential form of combining human and robot agents in a common task, but still faces a lack of freedom for the human agent. This paper proposes a Centroidal Voronoi Tessellation (CVT)-based road segmentation approach for brain-controlled robot navigation by means of asynchronous BCI. An electromyogram-based asynchronous mechanism is introduced into the BCI system for self-paced control. A novel CVT-based road segmentation method is provided to generate optional navigation goals in the road area for arbitrary goal selection. An event-related potential of the BCI is designed for target selection to communicate with the robot. The robot has an autonomous navigation function to reach the human selected goals. A comparison experiment in the single-step control pattern is executed to verify the effectiveness of the CVT-based asynchronous (CVT-A) BCI system. Eight subjects participated in the experiment, and they were instructed to control the robot to navigate toward a destination with obstacle avoidance tasks. The results show that the CVT-A BCI system can shorten the task duration, decrease the command times, and optimize navigation path, compared with the single-step pattern. Moreover, this shared control mechanism of the CVT-A BCI system contributes to the promotion of human and robot agent integration control in unstructured environments.
TI - CVT-Based Asynchronous BCI for Brain-Controlled Robot Navigation
JF - Cyborg and Bionic Systems
DO - 10.34133/cbsystems.0024
DA - 2023-04-18
UR - https://www.deepdyve.com/lp/pubmed-central/cvt-based-asynchronous-bci-for-brain-controlled-robot-navigation-TdtFEp0FOY
VL - 4
IS - 
DP - DeepDyve
ER -