InFuse Data Fusion Methodology for Space Robotics, Awareness and Machine Learning

Autor: Post, Mark, Michalec, Romain, Bianco, Alessandro, Yan, Xiu, de Maio, Andrea, Lacroix, Simon, Gancet, Jérémi, Govindaraj, Shashank, Martinez-Gonzalez, Xavier, Dalati, Iyas, Dominguez, Raúl, Wehbe, Bilal, Fabisch, Alexander, Röhrig, Enno, Souvannavong, Fabrice, Bissonnette, Vincent, Smíšek, Michal, Oumer, Nassir, Meyer, Lukas, Triebel, Rudolph, Márton, Zoltán-Csaba
Přispěvatelé: University of Strathclyde [Glasgow], Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Space Applications Services [Belgium], DFKI Bremen (DFKI), Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI), Magellium, Deutsches Zentrum für Luft- und Raumfahrt (DLR), European Project: 730014,Infusing data fusion for space robotics, Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Magellium (Magellium)
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: 69th International Astronautical Congress
69th International Astronautical Congress, Oct 2018, Bremen, Germany
Popis: International audience; Autonomous space vehicles such as orbital servicing satellites and planetary exploration rovers must be comprehensively aware of their environment in order to make appropriate decisions. Multi-sensor data fusion plays a vital role in providing these autonomous systems with sensory information of different types, from different locations, and at different times. The InFuse project, funded by the European Commission's Horizon 2020 Strategic Research Cluster in Space Robotics, provides the space community with an open-source Common Data Fusion Framework (CDFF) by which data may be fused in a modular fashion from multiple sensors. In this paper, we summarize the modular structure of this CDFF and show how it is used for the processing of sensor data to obtain data products for both planetary and orbital space robotic applications. Multiple sensor data from field testing that includes inertial measurements, stereo vision, and scanning laser range information is first used to produce robust multi-layered environmental maps for path planning. This information is registered and fused within the CDFF to produce comprehensive three-dimensional maps of the environment. To further explore the potential of the CDFF, we illustrate several applications of the CDFF that have been evaluated for orbital and planetary use cases of environmental reconstruction, mapping, navigation, and visual tracking. Algorithms for learning of maps, outlier detection, localization, and identification of objects are available within the CDFF and some early results from their use in space analogue scenarios are presented. These applications show how the CDFF can be used to provide a wide variety of data products for use by awareness and machine learning processes in space robots.
Databáze: OpenAIRE
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