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Planetary Robotics Vision Ground Processing
(PRoVisG)
Date du début: 1 oct. 2008,
Date de fin: 30 juin 2012
PROJET
TERMINÉ
PROVISG will build a framework for planetary robotic vision ground processing - develop the technology to better process and visualise existing & future data from planetary missions to maximize value-adedd exploitation of the data for research, technology and education - increase public awareness of such missions and the EC contribution to their scientific evaluation.We define robotic planetary space missions as unmanned missions performing in situ surface exploration on planetary objects. Most such missions involve mobility provided by a surface (‘rover’) or aerial (balloons etc.) vehicle and require rapid turnaround of imaging data through processing and proper presentation on the ground (i.e., on Earth) to make maximum use of the limited vehicle lifetime. PROVISG incorporates major EU and US research institutions & stakeholders involved in vision & navigation for robotic space missions and their scientific exploitation. We will develop a unified approach for robotic vision ground processing to establish a generic framework therefor.One main result will be a web-based GIS providing a comprehensive vision data processing chain and visualization of the context, history, vision meta data and -products of robotic planetary missions. For demonstration, a representative part of the US MER imagery will be processed to generate 2D and 3D data products (digital terrain models, mosaics, and a set of scientifically relevant results). Already available rover and aerobot mock-up equipment will be used in field test campaigns to verify and demonstrate the processing going beyond the vision abilities available so far at the MER and currently envisaged ESA missions. A summer school will be attached to the final test.Representative data sets will be publicly provided, allowing European institutions to test their processing on a competitive basis. The results will be presented at workshops supported by PROVISG, including a quantitative, systematic evaluation.
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