A robotic swarm can be defined as a large group of inexpensive, interchangeable

robots with limited sensing and/or actuating capabilities that cooperate (explicitly

or implicitly) based on local communications and sensing in order to complete a

mission. Its inherent redundancy provides flexibility and robustness to failures and

environmental disturbances which guarantee the proper completion of the required

task. At the same time, human intuition and cognition can prove very useful in

extreme situations where a fast and reliable solution is needed. This idea led to the

creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate

the human element into the control of robotic swarms for increased robustness and

reliability. The aim of the present work is to extend the current state-of-the-art in HSI

by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),

which has proven to be very useful for people with motor disabilities. At first, a

preliminary investigation about the connection of brain activity and the observation

of swarm collective behaviors is conducted. After showing that such a connection

may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.

The system is based on the combination of motor imagery and the input from a game

controller, while its feasibility is proven through an extensive experimental process.

Finally, speech imagery is proposed as an alternative mental task for BCI applications.

This is done through a series of rigorous experiments and appropriate data analysis.

This work suggests that the integration of BCI principles in HSI applications can be

successful and it can potentially lead to systems that are more intuitive for the users

than the current state-of-the-art. At the same time, it motivates further research in

the area and sets the stepping stones for the potential development of the field of

Brain-Swarm Interfaces (BSI).