| dc.contributor.advisor | Armando Solar-Lezama. | en_US |
| dc.contributor.author | Lynch, Alexander J.,M. Eng.Massachusetts Institute of Technology. | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2020-09-15T21:59:29Z | |
| dc.date.available | 2020-09-15T21:59:29Z | |
| dc.date.copyright | 2020 | en_US |
| dc.date.issued | 2020 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/127471 | |
| dc.description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020 | en_US |
| dc.description | Cataloged from the official PDF of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 73-74). | en_US |
| dc.description.abstract | In recent years there has been a dramatic increase in the use of personal drones in the general public, and with this increase in use has come an increase in research regarding the capabilities of these drones, particularly in the context of groups or "swarms" of drones attempting to collectively accomplish tasks. While exciting, this field requires either drones be operated and tested in the real world or through a simulation, and while the real world testing is often difficult to execute well, the alternative has been for each research group to develop their own simulation. This thesis proposes (1) a new framework meant to enable researchers to easily perform experiments in the context of drone swarms and (2) a novel problem that serves as an example of the type of problem the framework can assist in solving. | en_US |
| dc.description.statementofresponsibility | by Alexander J. Lynch. | en_US |
| dc.format.extent | 74 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | SwarmSim : a framework for execution and visualization of drone swarm simulations | en_US |
| dc.title.alternative | Swarm Sim : a framework for execution and visualization of drone swarm simulations | en_US |
| dc.title.alternative | Framework for execution and visualization of drone swarm simulations | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M. Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.identifier.oclc | 1192975056 | en_US |
| dc.description.collection | M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
| dspace.imported | 2020-09-15T21:59:27Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | EECS | en_US |