IRT Saint Exupéry pursues a series of portraits devoted to the men and women who best represent the institute: its researchers. Their high-level skills and wealth of experience contribute hugely to IRT Saint Exupéry’s performance and unique position, which is so crucial for its members and partners.
Can you tell us about your career?
After eight years, I wanted to move regions and improve my career prospects. I headed towards space imagery with Airbus Defence & Space, where I joined the department for processing remote sensing images obtained by satellite. Aside from the measurement chain, the techniques – removing noise, registering images or even detecting certain structures – were similar.
In 2016, I joined the mission planning department for earth observation satellites. The problem is to compute the image acquisition and downlink plan on the ground, relying on optimization algorithms that identify the best shots to be taken based on user requirements, while respecting the constraints linked to the satellite and its optical instrument.
These techniques are developed strongly at IRT Saint Exupéry.
Can you tell us more about your role on the IRT Saint Exupéry OCE project, which has yielded impressive results, and on the Synapse project that took over from it?
As part of OCE, we studied new decision-making techniques based on multi-agent systems and applied to planning a satellite constellation. This was the subject of Jonathan Bonnet’s PhD thesis, which he defended in 2017 (see news). If we consider a fleet of a dozen (or even a hundred) satellites, the issue of acquisition planning becomes extremely combinatorial, and we can’t solve it efficiently with a monolithic algorithm. Adaptive multi-agent approaches can be used to break the problem down and solve it via interactions between a large number of cooperative agents to bring out a global solution. We have benefited from a fruitful collaboration with researchers from the SMAC team at the IRIT laboratory since the OCE project, which is continuing with Synapse.
With this latter project, we’re focusing on the planning of large area coverage (countries and continents). To fully images such a large surface area, numerous basic acquisitions are needed, and you have to wait for a great many orbit revolutions of the different satellites. To reduce the coverage time and manage the satellite resource more efficiently, we use artificial intelligence algorithms to plan over the long term and to anticipate weather conditions, including the cloud cover that generates unusable images.
A current trend involves moving towards AI techniques, such as reinforcement learning. It’s a highly promising approach, developed in particular by Google DeepMind for the game of Go, which has generated a lot of buzz. By exploiting neural networks and decision-tree exploration techniques, the computer learns to improve via trial and error. For our large coverage problem, it will be all about choosing the best basic image acquisitions for each satellite so we can cover the zone as quickly as possible.
What impact has your time at IRT Saint Exupéry had on your career?
What results have been obtained?
Today, I’m still coming to IRT Saint Exupéry nearly half a day a week. I’m monitoring the work of the SYNAPSE project and supervised the PhD thesis of Timothée Jammot , which is taking on a very promising approach: to make the link between multi-agent techniques and those of reinforcement learning.
What do you like at IRT Saint Exupéry?
Do you have a small story to share with us?
It’s still pretty good to have left these half-empty prefabs behind, to have built a third wing and to have occupied the entire premises bit by bit, and then to have moved into this beautiful building, B612, where so much happens. It’s emblematic for Toulouse, which is becoming a major platform for research. Not to mention the arrival of former Minister Geneviève Fioraso as the new president of IRT Saint Exupéry, which is another strong sign.
Publications & Video
 Cooperative Multi-Agent Systems
 Institut de Recherche en Informatique de Toulouse (CNRS / INP Toulouse / Univ. Toulouse 3 Paul Sabatier / Univ. Toulouse 1 Capitole / Univ. Toulouse 2 Jean Jaurès)
 Meshing and Planning Large Area Acquisitions Support by Cooperative Multi-Agent Systems and Learning Techniques, IRT Saint Exupéry/ISAE-SUPAERO (2017-)