A system and a method for hybrid brain computer interface for controlling a robotic swarm are disclosed. The system comprises: a control interface for defining a plurality of electrodes configured for accessing a plurality of brain signals associated with a plurality of channels located over a sensorimotor cortex; a processor, in operative communication with the control interface, configured to: train a machine learning model to associate a brain state with data defining a brain signal, decode a control signal of the plurality of brain signals to generate control data, apply the control data to the machine learning model to identify the brain state, and transmit instructions to a plurality of robotic devices to modify a density of the plurality of robotic devices based on the brain state; and an input device, in operable communication with the processor, for generating input data, the input data utilized by the processor to modify a position of the plurality of robotic devices.
SYSTEMS AND METHODS FOR A HYBRID BRAIN INTERFACE FOR ROBOTIC SWARMS USING EEG SIGNALS AND AN INPUT DEVICE