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Sensor Artificial Intelligence and its Application to Space Systems - A White Paper

Börner, Anko and Hübers, Heinz-Wilhelm and Kao, Odej and Schmidt, Florian and Becker, Sören and Denzler, Joachim and Matolin, Daniel and Haber, David and Lucia, Sergio and Samek, Wojciech and Triebel, Rudolph and Eichstädt, Sascha and Biessmann, Felix and Kruspe, Anna and Jung, Peter and Kok, Manon and Gallego, Guillermo and Berger, Ralf (2020) Sensor Artificial Intelligence and its Application to Space Systems - A White Paper. Project Report. doi: 10.14279/depositonce-10185.

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Official URL: https://depositonce.tu-berlin.de/items/c7b7437e-21a5-45c2-827c-c8987d0a834a

Abstract

Information and communication technologies have accompanied our everyday life for years. A steadily increasing number of computers, cameras, mobile devices, etc. generate more and more data, but at the same time we realize that the data can only partially be analyzed with classical approaches. The research and development of methods based on artificial intelligence (AI) made enormous progress in the area of interpretability of data in recent years. With growing experience, both, the potential and limitations of these new technologies are increasingly better understood. Typically, AI approaches start with the data from which information and directions for action are derived. However, the circumstances under which such data are collected and how they change over time are rarely considered. A closer look at the sensors and their physical properties within AI approaches will lead to more robust and widely applicable algorithms. This holistic approach which considers entire signal chains from the origin to a data product, "Sensor AI", is a highly relevant topic with great potential. It will play a decisive role in autonomous driving as well as in areas of automated production, predictive maintenance or space research. The goal of this white paper is to establish "Sensor AI" as a dedicated research topic. We want to exchange knowledge on the current state-of-the-art on Sensor AI, to identify synergies among research groups and thus boost the collaboration in this key technology for science and industry.

Item URL in elib:https://elib.dlr.de/135254/
Document Type:Monograph (Project Report)
Title:Sensor Artificial Intelligence and its Application to Space Systems - A White Paper
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Börner, AnkoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hübers, Heinz-WilhelmUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kao, OdejTU BerlinUNSPECIFIEDUNSPECIFIED
Schmidt, FlorianTU BerlinUNSPECIFIEDUNSPECIFIED
Becker, SörenTU BerlinUNSPECIFIEDUNSPECIFIED
Denzler, JoachimFSU Jenahttps://orcid.org/0000-0002-3193-3300UNSPECIFIED
Matolin, DanielPropheseeUNSPECIFIEDUNSPECIFIED
Haber, DavidDaedalanUNSPECIFIEDUNSPECIFIED
Lucia, SergioTU Berlinhttps://orcid.org/0000-0002-3347-5593UNSPECIFIED
Samek, WojciechHHIUNSPECIFIEDUNSPECIFIED
Triebel, RudolphUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Eichstädt, SaschaPTBUNSPECIFIEDUNSPECIFIED
Biessmann, FelixBeuth Hochschule BerlinUNSPECIFIEDUNSPECIFIED
Kruspe, AnnaUNSPECIFIEDhttps://orcid.org/0000-0002-2041-9453UNSPECIFIED
Jung, PeterTU Berlinhttps://orcid.org/0000-0001-7679-9697UNSPECIFIED
Kok, ManonDelft University of TechnologyUNSPECIFIEDUNSPECIFIED
Gallego, GuillermoTU BerlinUNSPECIFIEDUNSPECIFIED
Berger, RalfUNSPECIFIEDhttps://orcid.org/0000-0002-1314-5554UNSPECIFIED
Date:9 June 2020
Refereed publication:Yes
Open Access:Yes
DOI:10.14279/depositonce-10185
Status:Published
Keywords:Sensor, Artificial Intelligence
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Project MOREX [SY]
Location: Berlin-Adlershof , Jena , Oberpfaffenhofen
Institutes and Institutions:Institute of Optical Sensor Systems
Institute of Robotics and Mechatronics (since 2013)
Institute of Data Science
Deposited By: Börner, Anko
Deposited On:28 Mar 2023 16:02
Last Modified:28 Mar 2023 16:04

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