Image selection algorithm for GMES mission
Oct 12, 2009
Stuart Grey and Gianmarco Radice and Massimiliano Vasile and Joris Fuchs and Quirijn Wisjnands
60th International Astronautical Congress (IAC 2009), Daejeon, Republic of Korea, 12–16 Oct 2009, pp. 2382–2387
ISBN: 978-1-61567-908-9
This paper outlines the user interface and image selection algorithm developed as part of the multi agent system segment of the Global Monitoring for Environment and Security (GMES) European Space Agency mission. The objective of GMES is to pull together and rationalise all the information obtained by environmental satellites, air and ground stations to provide a comprehensive picture of the health of Earth for both environmental and security purposes. A multi-agent system (MAS) is being developed to coordinate and integrate the many types of data sources, specifically the multiple different classes of Earth monitoring satellites including both planned missions and satellites currently in operation. This paper presents the development of an image selection algorithm and associated user interface for requesting images of the Earth from the heterogeneous satellite constellation. When a user request is made it is sent to the MAS, specifically the image broker agent where bids from the agents responsible for each satellite are received. The image selection algorithm is designed to assess each of these bids and to display the images that most closely match the users' criteria. A key problem solved by this algorithm is the case when there are no images that meet the user requirements. In this case the algorithm suggests to the user where constraints and variables could be relaxed to allow a valid image to be produced. This step is separate from the initial ranking of the images for the user and is carried out using a global optimisation approach. The user interface and image selection algorithm allow a user to easily request images from the system without any prior knowledge of coverage and satellite capabilities and occurs in near real time, offering a substantial improvement over current systems and helping to maximise the benefits offered by using a MAS.