EffFeu Project: Towards Mission-Guided Application of Drones in Safety and Security Environments
dc.contributor.author | Hrabia, Christopher-Eyk | |
dc.contributor.author | Hessler, Axel | |
dc.contributor.author | Xu, Yuan | |
dc.contributor.author | Seibert, Jacob | |
dc.contributor.author | Brehmer, Jan | |
dc.contributor.author | Albayrak, Sahin | |
dc.date.accessioned | 2019-03-04T10:42:05Z | |
dc.date.available | 2019-03-04T10:42:05Z | |
dc.date.issued | 2019-02-25 | |
dc.description.abstract | The number of unmanned aerial system (UAS) applications for supporting rescue forces is growing in recent years. Nevertheless, the analysis of sensed information and control of unmanned aerial vehicle (UAV) creates an enormous psychological and emotional load for the involved humans especially in critical and hectic situations. The introduced research project EffFeu (Efficient Operation of Unmanned Aerial Vehicle for Industrial Firefighters) especially focuses on a holistic integration of UAS in the daily work of industrial firefighters. This is done by enabling autonomous mission-guided control on top of the presented overall system architecture, goal-oriented high-level task control, comprehensive localisation process combining several approaches to enable the transition from and to GNSS-supported and GNSS-denied environments, as well as a deep-learning based object recognition of relevant entities. This work describes the concepts, current stage, and first evaluation results of the research project. | en |
dc.description.sponsorship | DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berlin | en |
dc.description.sponsorship | BMBF, 13N14093, Verbundprojekt: Effizienter Einsatz von unbemannten Flugsystemen für Werkfeuerwehren (EffFeu) - Teilvorhaben: Intelligente Unbemannte Flugsysteme | de |
dc.identifier.eissn | 1424-8220 | |
dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/9193 | |
dc.identifier.uri | http://dx.doi.org/10.14279/depositonce-8279 | |
dc.language.iso | en | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject.ddc | 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten | de |
dc.subject.other | decisional autonomy | en |
dc.subject.other | decision-making | en |
dc.subject.other | planning | en |
dc.subject.other | object recognition | en |
dc.subject.other | deep learning | en |
dc.subject.other | GNSS-denied localisation | en |
dc.title | EffFeu Project: Towards Mission-Guided Application of Drones in Safety and Security Environments | en |
dc.type | Article | en |
dc.type.version | publishedVersion | en |
dcterms.bibliographicCitation.articlenumber | 973 | en |
dcterms.bibliographicCitation.doi | 10.3390/s19040973 | en |
dcterms.bibliographicCitation.issue | 4 | en |
dcterms.bibliographicCitation.journaltitle | Sensors | en |
dcterms.bibliographicCitation.originalpublishername | MDPI | en |
dcterms.bibliographicCitation.originalpublisherplace | Basel | en |
dcterms.bibliographicCitation.volume | 19 | en |
tub.accessrights.dnb | free | en |
tub.affiliation | Fak. 4 Elektrotechnik und Informatik::Inst. Wirtschaftsinformatik und Quantitative Methoden::FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT) | de |
tub.affiliation.faculty | Fak. 4 Elektrotechnik und Informatik | de |
tub.affiliation.group | FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT) | de |
tub.affiliation.institute | Inst. Wirtschaftsinformatik und Quantitative Methoden | de |
tub.publisher.universityorinstitution | Technische Universität Berlin | en |