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

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

Electronic Engineering

Research output: Contribution to conference › Paper › peer-review

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 language	English
Number of pages	8
Publication status	Published - 4 Jun 2018
Event	International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, i-SAIRAS 2018 - Duration: 4 Jun 2018 → 6 Jun 2018

Conference

Conference	International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, i-SAIRAS 2018
Period	4/06/18 → 6/06/18

Keywords

space robotics, data fusion, autonomous systems, data architecture

Access to Document

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

Cite this

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, i-SAIRAS 2018. https://atpi.eventsair.com/QuickEventWebsitePortal/isairas2018/isairas-2018

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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.",

keywords = "space robotics, data fusion, autonomous systems, data architecture",

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

year = "2018",

month = jun,

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language = "English",

note = "International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, i-SAIRAS 2018 ; Conference date: 04-06-2018 Through 06-06-2018",

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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, i-SAIRAS 2018, 4/06/18 - 6/06/18. <https://atpi.eventsair.com/QuickEventWebsitePortal/isairas2018/isairas-2018>

TY - CONF

T1 - A common data fusion framework for space robotics

T2 - International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, i-SAIRAS 2018

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

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AB - 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.

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