OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18173 Abstract-Mission planning for a constellation of Earth observation satellites is a complex problem raising significant technological challenges for tomorrow's space systems. The large numbers of customers requests and their dynamic introduction in the planning system result in a huge combinatorial search space with a potentially highly dynamical evolution requirements. The techniques used nowadays have several limitations, in particular, it is impossible to dynamically adapt the plan during its construction even for small modifications. Satellites of a constellation are planned in a chronological way instead of a more collective planning which can provide additional load balancing.In this paper, we propose to solve this difficult and highly dynamic problem using adaptive multi-agent systems, taking advantage from their self-adaptation and self-organization mechanisms. In the proposed system, the agents, through their local interactions, allow to dynamically reach a good solution, while ensuring a controlled distribution of tasks within the constellation of satellites. Finally, a comparison with a classical chronological greedy algorithm, commonly used in the spatial domain, highlights the advantages of the presented system.

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La planification de missions de constellations de satellites est un problème complexe soulevant d'importants défis technologiques pour les systèmes de demain. Le grand nombre de demandes clients et leurs arrivées dynamiques implique une combinatoire et une dynamique très élevées. Les techniques actuellement utilisées présentent plusieurs limites, il est notamment impossible d'adapter dynamiquement le plan lors de sa construction, et les satellites sont traités individuellement de façon chronologique, ce qui minimise l'apport de la constellation. Dans cet article, nous proposons de résoudre ce problème difficile et dynamique à l'aide de systèmes multi-agents adaptatifs, profitant de leurs mécanismes d'auto-adaptation et d'autoorganisation. Ainsi, les interactions locales permettent d'atteindre dynamiquement une bonne solution. Enfin, une comparaison avec un algorithme glouton chronologique, couramment utilisée dans le domaine spatial, met en évidence les avantages du système présenté. ABSTRACT. Mission planning for a constellation of satellites is a complex problem raising significant technological challenges for tomorrow's space systems. The large numbers of customers requests and their dynamic introduction result in a huge combinatorial search space. Today's techniques have several limitations, in particular, it is impossible to dynamically adapt the plan during its construction, and satellites are planned in a chronological way instead of a more collective planning which can provide additional load balancing. In this paper, we propose to solve this difficult and dynamic problem using adaptive multi-agent systems, taking advantage from their self-adaptation and self-organization mechanisms. Thus, local interactions allow to dynamically reach a good solution. Finally, a comparison with a chronological greedy algorithm, commonly used in the spatial domain, highlights the advantages of the presented system.