InFuse : a comprehensive framework for data fusion in space robotics
Shashank Govinderaj, Jérémi Gancet, Mark Post, Raúl Domínguez, Fabrice Souvannavong, Simon Lacroix, Michal Smíšek, Javier Hidalgo‐Carrió, Bilal Wehbe, Alexander Fabisch, Andrea De Maio, Nassir W. Oumer, Vincent Bissonnette, Zoltán-Csaba Márton, Sandeep Kottath, Christian Nissler, Xiu-Tian Yan, Rudolph Triebel, Francesco Nuzzolo
- Year
- 2017
- Citations
- 2
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).
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991