2026-05-24T20:41:01Zhttps://keep.lib.asu.edu/oai/requestoai:keep.lib.asu.edu:node-1557222024-12-20T18:25:12Zoai_pmh:alloai_pmh:repo_items155722
https://hdl.handle.net/2286/R.I.45014
http://rightsstatements.org/vocab/InC/1.0/
All Rights Reserved
2017
2019-08-01T08:07:39
ix, 93 pages : illustrations (some color)
Masters Thesis
Academic theses
Text
eng
Karavas, Georgios Konstantinos
Artemiadis, Panagiotis
Berman, Spring M.
Lee, Hyunglae
Arizona State University
Partial requirement for: M.S., Arizona State University, 2017
Includes bibliographical references (pages 80-87)
Field of study: Mechanical engineering
A robotic swarm can be defined as a large group of inexpensive, interchangeable<br/><br/>robots with limited sensing and/or actuating capabilities that cooperate (explicitly<br/><br/>or implicitly) based on local communications and sensing in order to complete a<br/><br/>mission. Its inherent redundancy provides flexibility and robustness to failures and<br/><br/>environmental disturbances which guarantee the proper completion of the required<br/><br/>task. At the same time, human intuition and cognition can prove very useful in<br/><br/>extreme situations where a fast and reliable solution is needed. This idea led to the<br/><br/>creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate<br/><br/>the human element into the control of robotic swarms for increased robustness and<br/><br/>reliability. The aim of the present work is to extend the current state-of-the-art in HSI<br/><br/>by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),<br/><br/>which has proven to be very useful for people with motor disabilities. At first, a<br/><br/>preliminary investigation about the connection of brain activity and the observation<br/><br/>of swarm collective behaviors is conducted. After showing that such a connection<br/><br/>may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.<br/><br/>The system is based on the combination of motor imagery and the input from a game<br/><br/>controller, while its feasibility is proven through an extensive experimental process.<br/><br/>Finally, speech imagery is proposed as an alternative mental task for BCI applications.<br/><br/>This is done through a series of rigorous experiments and appropriate data analysis.<br/><br/>This work suggests that the integration of BCI principles in HSI applications can be<br/><br/>successful and it can potentially lead to systems that are more intuitive for the users<br/><br/>than the current state-of-the-art. At the same time, it motivates further research in<br/><br/>the area and sets the stepping stones for the potential development of the field of<br/><br/>Brain-Swarm Interfaces (BSI).
Engineering
Neurosciences
Computer Science
Brain Computer Interfaces
Human Swarm Interfaces
Swarms
Brain-Computer Interfaces
Human-Robot Interaction
Swarm Intelligence
Brain computer interfaces for the control of robotic swarms