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InFuse : a comprehensive framework for data fusion in space robotics

Shashank Govinderaj; Jeremi Gancet; Mark Post; Raúl Domínguez; Fabrice Souvannavong; Simon Lacroix; Michal Smisek; Javier Hidalgo-Carrio; Bilal Wehbe; Alexander Fabisch; Andrea De Maio; Nassir Oumer; Vincent Bissonnette; Zoltan-Csaba Marton; Sandeep Kottath; Christian Nissler; Xiu Yan; Rudolph Triebel; Francesco Nuzzolo
In: Proceedings of ASTRA 2017, ESA-ESTEC. ESA/Estec Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA-2017), June 20-22, Leiden, Netherlands, 2017.

Abstract

Fused sensory data provides decision-making processes with exploitable information about the external environment and a robot's internal state. This paper describes some preliminary work on the InFuse project to create a modular and portable data fusion system funded by European Commission's Horizon 2020 Strategic Research Cluster on Space Robotics Technologies. In space robotics, a wide range of data fusion techniques are required to accomplish challenging objectives for exploration, science and commercial purposes. This includes navigation for planetary and orbital robotics, scientific data gathering, and on-orbit spacecraft servicing applications. InFuse aims to develop a comprehensive open-source data fusion toolset to combine and interpret sensory data from multiple robotic sensors, referred as a Common Data Fusion Framework (CDFF).

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