InFuse aims to develop a comprehensive data fusion toolset for robot sensors (aka Common Data Fusion Framework, or CDFF) that will serve in the context of many space robotics applications, on planetary surface as well as in orbit or other space environments. The InFuse CDFF will be developed relying on the expertise of partners having substantial experience with a wide range of sensors data handling and processing techniques (perception and navigation related) and a wide range of robotic applications – both in space and terrestrial conditions.
|Duration:||01.11.2016 till 31.01.2019|
|Partner:||Space Applications Services NV., Deutsches Zentrum für Luft- und, Raumfahrt, Magellium, Strathclyde University, Laboratoire d’Analyse et d’Architecture des Systèmes|
Team VII - Sustained Interaction & Learning
Team VIII - Knowledge-based long-term Autonomy
|Application Field:||Space Robotics|
European Space Robot Control Operating System (11.2016- 01.2019)
Signal Processing and Classification Environment written in PythonRock
Robot Construction Kit
InFuse is a European project developed in the context of the Horizon 2020 PERASPERA (Plan European Roadmap and Activities for Space Exploitation of Robotics and Autonomy) call on Space Robotics Challenges (SRC). Inside the SRC the projects are referred as Operational Grants (OG) and each one focusses to a particular open challenge in the Space Robotics development.
InFuse makes provision for a convenient and effective articulation with the other Horizon 2020 Space Robotics Challenge (SRC) common building blocks – in particular: OG1 (RCOS), OG2 (Autonomy Framework) and OG4 (Inspection Sensor Suite). The solution proposed in InFuse to wrap and handle data fusion techniques and their produced data will make their adoption easy and effective by a wide range of users, both among the SRC stakeholders and in the wider space robotics community. In particular, InFuse will not only provide access to an extensive set of robust data fusion capabilities, relevant both for On-Orbit and planetary scenarios, but will also include a data fusion orchestration and products management tool allowing to control the data fusion processes and to retrieve conveniently (on-demand) products such as maps, models of the environment or objects, science relevant data, etc.
The potential impact of InFuse is huge, as such a tool will be relevant and useful in a wide range of robotic applications and user communities – not only in the Space Robotics SRC activities and more widely in the space robotics area, but also in many non-space domains (e.g. marine, aerial, terrestrial robotic applications). No such comprehensive data tool exists so far: InFuse will be a European asset that many industrial, research and academic roboticists in Europe (and farther) may benefit from.