Search of shipwrecked people using drone swarms

dc.contributor.advisorBarth, Fabrício Jailson
dc.contributor.authorDamiani, Enrico Francesco
dc.contributor.authorAbreu, Leonardo Duarte Malta de
dc.contributor.authorCarrete, Luis Filipe Sanchez
dc.contributor.authorCastanares, Manuel
dc.creatorDamiani, Enrico Francesco
dc.creatorAbreu, Leonardo Duarte Malta de
dc.creatorCarrete, Luis Filipe Sanchez
dc.creatorCastanares, Manuel
dc.date.accessioned2024-08-13T19:43:26Z
dc.date.available2024-08-13T19:43:26Z
dc.date.issued2023
dc.descriptionProjeto realizado para a empresa Embraer - Mentor na empresa: José Fernando Basso Brancalion
dc.description.abstractThe aim of this project is to develop a reinforcement learning algorithm with its purpose being to find shipwrecked people using a swarm of drones. A simulated environment was also developed to train and visualize the outcome of the trained algorithm. This project does not discuss image recognition of shipwrecked people, since the true focus of this project is to optimize the search routine of a drone to find the target in the quickest way possible. The implemented Reinforce algorithm takes into account a dynamic map of probabilities, representing the chances of a person being found, as well as the position of other agents. Keywords: Multi-agent; Reinforcement learning, Shipwrecked people; Drone swarms.en
dc.formatDigital
dc.format.extent49 p.
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/6780
dc.language.isoen
dc.subjectMulti-agenten
dc.subjectReinforcement learningen
dc.subjectShipwrecked peopleen
dc.subjectDrone swarmsen
dc.titleSearch of shipwrecked people using drone swarms
dspace.entity.typePublication
local.contributor.boardmemberBarth, Fabrício Jailson
local.contributor.boardmemberKurauchi, Andrew Toshiaki Nakayama
local.contributor.boardmemberFABIO JOSE AYRES
local.subject.cnpqCIENCIAS SOCIAIS APLICADAS
relation.isBoardMemberOfPublication37971022-7c69-4e93-9186-4c9431a1f95c
relation.isBoardMemberOfPublication.latestForDiscovery37971022-7c69-4e93-9186-4c9431a1f95c
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