A common data fusion framework for space robotics: architecture and data fusion methods

Raul Dominguez, Shashank Govindaraj, Jeremi Gancet, Mark Post, Romain Michalec, Nassir Oumer, Bilal Wehbe, Alessandro Bianco, Alexander Fabisch, Simon Lacroix, Andrea De Maio, Quentin Labourey, Fabrice Souvannavong, Vincent Bissonnette, Michal Smisek, Xiu Yan

Research output: Contribution to conferencePaper

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Abstract

Data fusion algorithms make it possible to combine data from different sensors into symbolic representations such as environment maps, object models, and position estimates. The software community in space robotics lacks a comprehensive software framework to fuse and contextually store data from multiple sensors while also making it easier to develop, evaluate, and compare algorithms. The InFuse consortium, six partners in the industrial and academic space sector working under the supervision of a Program Support Activity (PSA) consisting of representatives from ESA, ASI, CDTI, CNES, DLR, UKSA, is developing such a framework, complete with a set of data fusion implementations based on state-of-the-art perception, localization and mapping algorithms, and performance metrics to evaluate them. This paper describes the architecture of this Common Data Fusion Framework and overviews the data fusion methods that it will provide for tasks such as localisation, mapping, environment reconstruction, object detection and tracking.
Original languageEnglish
Number of pages9
Publication statusPublished - 4 Jun 2018
Event International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia - Madrid, Spain
Duration: 4 Jun 20186 Jun 2018
Conference number: 14th
https://atpi.eventsair.com/QuickEventWebsitePortal/isairas2018/isairas-2018

Conference

Conference International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia
Abbreviated titlei-SAIRAS 2018
CountrySpain
CityMadrid
Period4/06/186/06/18
Internet address

Keywords

  • space robotics
  • data fusion
  • autonomous systems
  • data architecture

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    Dominguez, R., Govindaraj, S., Gancet, J., Post, M., Michalec, R., Oumer, N., ... Yan, X. (2018). A common data fusion framework for space robotics: architecture and data fusion methods. Paper presented at International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, Madrid, Spain.