EO constellation MPS based on ant colony optimization algorithms

Missions involving multiple spacecraft can offer a number of benefits over single platforms. Earth Observation (EO) constellations have the potential to offer critical services for the society such as global monitoring and disaster management. This trend is opening new challenges to the automated Mission Planning & Scheduling (MPS) systems aiming at gaining maximum value from the constellations, by increasing the overall efficiency and the system responsiveness. In this paper, we describe an innovative ground-based automated planning & scheduling system for multiple platforms. The mission used as target for our design is the Disaster Monitoring Constellation, the first Earth Observation constellation of low cost small satellites. The novelty of this project is in designing an MPS as self-organizing multi agent architecture, inspired by Ant Colony Optimization algorithms, offering a system adaptable to the problem changes and able to synchronize the satellites' plans in order to avoid duplications.

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