Atlas Fusion - Modern Framework for Autonomous Agent Sensor Data Fusion

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dc.contributor.authorLigocki, Adamcs
dc.contributor.authorJelínek, Alešcs
dc.contributor.authorŽalud, Luděkcs
dc.date.issued2022-05-23cs
dc.description.abstractIn this paper, we present our new sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's surrounding environment by fusing a wide range of various sensors into the data model that we can use as a basement for the decision making and planning algorithms. Our software currently covers the data fusion of the RGB and thermal cameras, 3D LiDARs, 3D IMU, and a GNSS positioning. The framework covers a complete pipeline from data loading, filtering, preprocessing, environment model construction, visualization, and data storage. The architecture allows the community to modify the existing setup or to extend our solution with new ideas. The entire software is fully compatible with ROS (Robotic Operation System), which allows the framework to cooperate with other ROS-based software. The source codes are fully available as an open-source under the MIT license. See https://github.com/Robotics-BUT/Atlas-Fusion. Index Terms—Open Source, Autonomous Agent, Self Driving Car, Sensor Fusion, Mapping, ROSen
dc.formattextcs
dc.format.extent1-6cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citation14th International Conference ELEKTRO, ELEKTRO 2022 - Proceedings. 2022, p. 1-6.en
dc.identifier.doi10.1109/ELECTRO53996.2022.9803587cs
dc.identifier.isbn978-1-66-546726-1cs
dc.identifier.orcid0000-0002-6813-4318cs
dc.identifier.orcid0000-0001-7519-2092cs
dc.identifier.orcid0000-0003-2993-7772cs
dc.identifier.other180792cs
dc.identifier.researcheridA-7047-2012cs
dc.identifier.scopus8439091900cs
dc.identifier.urihttp://hdl.handle.net/11012/209123
dc.language.isoencs
dc.publisherIEEEcs
dc.relationEuropean Union (EU) & "Horizon 2020"
dc.relation.ispartof14th International Conference ELEKTRO, ELEKTRO 2022 - Proceedingscs
dc.relation.projectIdinfo:eu-repo/grantAgreement/EC/H2020/857306/EU//RICAIP
dc.relation.projectIdinfo:eu-repo/grantAgreement/EC/H2020/826653/EU//NewControl
dc.relation.urihttps://ieeexplore.ieee.org/document/9803587cs
dc.rights(C) IEEEcs
dc.rights.accessopenAccesscs
dc.subjectOpen Sourceen
dc.subjectAutonomous Agenten
dc.subjectSelf Driving Caren
dc.subjectSensor Fusionen
dc.subjectMappingen
dc.subjectROSen
dc.titleAtlas Fusion - Modern Framework for Autonomous Agent Sensor Data Fusionen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionacceptedVersionen
sync.item.dbidVAV-180792en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:50:43en
sync.item.modts2025.01.17 15:15:07en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika a robotikacs
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