InFuse data fusion methodology for space robotics, awareness and machine learning

Post, Mark and Michalec, Romain and Bianco, Alessandro and Yan, Xiu-Tian and De Maio, Andrea and Labourey, Quentin and Lacroix, Simon and Gancet, Jeremi and Govindaraj, Shashank and Marinez-Gonazalez, Xavier and Dominguez, Raul and Wehbe, Bilal and Fabich, Alexander and Souvannavong, Fabrice and Bissonnette, Vincent and Smisek, Michal and Oumer, Nassir W. and Triebel, Rudolph and Marton, Zoltan-Csaba (2018) InFuse data fusion methodology for space robotics, awareness and machine learning. In: 69th International Astronautical Congress, 2018-10-01 - 2018-10-05. (In Press)

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    Abstract

    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.

    Author(s):Post, Mark ORCID logoORCID: https://orcid.org/0000-0002-1925-7039, Michalec, Romain, Bianco, Alessandro ORCID logoORCID: https://orcid.org/0000-0003-2273-7823, Yan, Xiu-Tian ORCID logoORCID: https://orcid.org/0000-0002-3798-7414, De Maio, Andrea, Labourey, Quentin, Lacroix, Simon, Gancet, Jeremi, Govindaraj, Shashank, Marinez-Gonazalez, Xavier, Dominguez, Raul, Wehbe, Bilal, Fabich, Alexander, Souvannavong, Fabrice, Bissonnette, Vincent, Smisek, Michal, Oumer, Nassir W., Triebel, Rudolph and Marton, Zoltan-Csaba
    Item type:Conference or Workshop Item(Paper)
    ID code:64033
    Keywords:space vehicles, space robotics, planetary exploration, Motor vehicles. Aeronautics. Astronautics, Aerospace Engineering
    Subjects:Technology > Motor vehicles. Aeronautics. Astronautics
    Department:Faculty of Engineering > Design, Manufacture and Engineering Management
    Depositing user: Pure Administrator
    Date deposited:14 May 2018 11:05
    Last modified:16 Jan 2020 02:25
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/64033
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