By the same authors

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

Research output: Contribution to conferencePaper

Author(s)

  • Mark Post
  • Romain Michalec
  • Alessandro Bianco
  • Xiu-Tian Yan
  • Andrea De Maio
  • Quentin Labourey
  • Simon Lacroix
  • Jeremi Gancet
  • Shashank Govindaraj
  • Xavier Marinez-Gonazalez
  • Raul Dominguez
  • Bilal Wehbe
  • Alexander Fabich
  • Fabrice Souvannavong
  • Vincent Bissonnette
  • Michal Smisek
  • Nassir W. Oumer
  • Rudolph Triebel
  • Zoltan-Csaba Marton

Department/unit(s)

Conference

Conference69th International Astronautical Congress, IAC 2018
Conference date(s)1/10/185/10/18

Publication details

DatePublished - 26 Apr 2018
Original languageEnglish

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.

    Research areas

  • space vehicles, space robotics, planetary exploration

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