A BCI-Based Motion Control System for Heterogeneous Robot Swarm

Abstract

The study presents a method to construct a brain-computer interaction (BCI) motion control system that uses human brainwave signals to control the motion of different kinds of individuals in a heterogeneous robot swarm. Through establishing the BCI system based on Stable State Visual Evoked Potential (SSVEP), the virtual reality (VR) twin scene for monitoring the operating state and the external environment of robots and the heterogeneous robot swarm composed of unmanned drones and vehicles, the direct motion control of human brain wave signals on heterogeneous robot swarms is realized. The experimental results present that the subjects can apply the system to achieve motion control of a heterogeneous robot swarm in a simulated complex obstacle avoidance scenario with a 90% obstacle avoidance success rate. The system provides a new control method for traditional heterogeneous robot swarm motion systems, and also provides a new solution for how to deal with sophisticated and versatile application scenarios, which is significant for improving the system's perception capability, decision-making ability, and intelligence level.