Brain-Machine Interfaces (BMIs) have been one of the most
influential and disruptive science fields of the past decades. Prosthetic orremotely operated robotic devices being controlled by brain signals hastransitioned from science fiction to reality. Advances in the recording
electrodes technology and the machine learning and signal decoding algorithms
were critical in the realization of those systems. The second decade of the
21st century brings new challenges found in both frontiers; first, advancements
in neuroscience are sought via high-resolution mapping of the brain for better
understanding of its function and decision making processes.
On the robotics
frontiers, the challenge of the human controlling many robots simultaneously is
of utmost importance for applications spanning from industrial and
entertainment, to disaster response and military. As the swarming paradigm,
deriving inspiration from the behaviour of natural swarms such as bird flocks
and fish schools, offers myriad advantages to a team of robots, the way humans
interact and control a robotic swarm creates new avenues of research. This
article summarizes recent developments and novel methods for brain-swarm
interfaces, and poses challenges for the future researchers.(Read more)

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