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This work presents a novel marriage of Swarm Robotics and Brain ComputerInterface technology to produce an interface which connects a user to a swarmof robots. The proposed interface enables the user to control the swarm's sizeand motion employing just thoughts and eye movements. The thoughts and eyemovements are recorded as electrical signals from the scalp by an off-the-shelfElectroencephalogram (EEG) headset. Signal processing techniques are used tofilter out noise and decode the user's eye movements from raw signals, while aHidden Markov Model technique is employed to decipher the user's thoughts fromfiltered signals. The dynamics of the robots are controlled using a swarmcontroller based on potential fields. The shape and motion parameters of thepotential fields are modulated by the human user through the brain-swarminterface to move the robots. The method is demonstrated experimentally with ahuman controlling a swarm of three M3pi robots in a laboratory environment, aswell as controlling a swarm of 128 robots in a computer simulation.

Brain-Swarm Interface (BSI): Controlling a Swarm of Robots with Brain and Eye Signals from an EEG Headset