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

Abstract

Data fusion algorithms provide a system with the capacity to combine the data from different sensors and metadata (e.g. timestamps, geometric models) into into symbolic representations like maps or position estimations. Software that implements these algorithms needs to provide a solution to the challenge of awareness using multiple sensors faced by robots and autonomous systems as well as the means to access and store this data for future uses. The software community in space robotics lacks a common framework to make developing, reusing and comparing data fusion solutions easier. InFuse provides that framework, and not only a set of data fusion solutions based on state-of-the-art algorithms, but also performance metrics to qualify algorithms. InFuse is developed by six industrial and academic partners working in the space sector, under the supervision of several European space agencies (ASI, CDTI, CNES, DLR, ESA, UK Space). This paper describes the architecture and the methods of the robot perception and localization framework InFuse Operational Grant 3 (OG3), in order to provide the Space Robotics community with a Common Data Fusion Framework (CDFF).

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

Fingerprint

Data fusion
Robotics
Robots
Sensors
Metadata

Keywords

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

Cite this

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.
Dominguez, Raul ; Govindaraj, Shashank ; Gancet, Jeremi ; Post, Mark ; Michalec, Romain ; Oumer, Nassir ; Wehbe, Bilal ; Bianco, Alessandro ; Fabisch, Alexander ; Lacroix, Simon ; De Maio, Andrea ; Labourey, Quentin ; Souvannavong, Fabrice ; Bissonnette, Vincent ; Smisek, Michal ; Yan, Xiu. / 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.9 p.
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Dominguez, R, Govindaraj, S, Gancet, J, Post, M, Michalec, R, Oumer, N, Wehbe, B, Bianco, A, Fabisch, A, Lacroix, S, De Maio, A, Labourey, Q, Souvannavong, F, Bissonnette, V, Smisek, M & 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, 4/06/18 - 6/06/18, .

A common data fusion framework for space robotics : architecture and data fusion methods. / Dominguez, Raul; Govindaraj, Shashank; Gancet, Jeremi; Post, Mark; Michalec, Romain; Oumer, Nassir; Wehbe, Bilal; Bianco, Alessandro; Fabisch, Alexander; Lacroix, Simon; De Maio, Andrea; Labourey, Quentin; Souvannavong, Fabrice; Bissonnette, Vincent; Smisek, Michal; Yan, Xiu.

2018. Paper presented at International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, Madrid, Spain.

Research output: Contribution to conferencePaper

TY - CONF

T1 - A common data fusion framework for space robotics

T2 - architecture and data fusion methods

AU - Dominguez,Raul

AU - Govindaraj,Shashank

AU - Gancet,Jeremi

AU - Post,Mark

AU - Michalec,Romain

AU - Oumer,Nassir

AU - Wehbe,Bilal

AU - Bianco,Alessandro

AU - Fabisch,Alexander

AU - Lacroix,Simon

AU - De Maio,Andrea

AU - Labourey,Quentin

AU - Souvannavong,Fabrice

AU - Bissonnette,Vincent

AU - Smisek,Michal

AU - Yan,Xiu

PY - 2018/6/4

Y1 - 2018/6/4

N2 - Data fusion algorithms provide a system with the capacity to combine the data from different sensors and metadata (e.g. timestamps, geometric models) into into symbolic representations like maps or position estimations. Software that implements these algorithms needs to provide a solution to the challenge of awareness using multiple sensors faced by robots and autonomous systems as well as the means to access and store this data for future uses. The software community in space robotics lacks a common framework to make developing, reusing and comparing data fusion solutions easier. InFuse provides that framework, and not only a set of data fusion solutions based on state-of-the-art algorithms, but also performance metrics to qualify algorithms. InFuse is developed by six industrial and academic partners working in the space sector, under the supervision of several European space agencies (ASI, CDTI, CNES, DLR, ESA, UK Space). This paper describes the architecture and the methods of the robot perception and localization framework InFuse Operational Grant 3 (OG3), in order to provide the Space Robotics community with a Common Data Fusion Framework (CDFF).

AB - Data fusion algorithms provide a system with the capacity to combine the data from different sensors and metadata (e.g. timestamps, geometric models) into into symbolic representations like maps or position estimations. Software that implements these algorithms needs to provide a solution to the challenge of awareness using multiple sensors faced by robots and autonomous systems as well as the means to access and store this data for future uses. The software community in space robotics lacks a common framework to make developing, reusing and comparing data fusion solutions easier. InFuse provides that framework, and not only a set of data fusion solutions based on state-of-the-art algorithms, but also performance metrics to qualify algorithms. InFuse is developed by six industrial and academic partners working in the space sector, under the supervision of several European space agencies (ASI, CDTI, CNES, DLR, ESA, UK Space). This paper describes the architecture and the methods of the robot perception and localization framework InFuse Operational Grant 3 (OG3), in order to provide the Space Robotics community with a Common Data Fusion Framework (CDFF).

KW - space robotics

KW - data fusion

KW - autonomous systems

KW - data architecture

UR - https://atpi.eventsair.com/QuickEventWebsitePortal/isairas2018/isairas-2018

M3 - Paper

ER -

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