The Earth Observation market is growing rapidly, along with the missions' complexity. Therefore, automated Mission Planning systems are being designed, allowing for operators to simply specify their intentions on a high level. In this paper, we propose an automated Mission Planning System based on the ants' foraging mechanism and apply it to two different mission planning problems, from an Earth Imaging and a Data Relay mission, investigating the system's ability to be generalised. We compare the planning process for the two problems and generalise on the type of planning problems the system can address.
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.
Distributed missions have become of great interest in the last decade as they offer a number of potential benefits for Earth Observation, especially global monitoring and disaster management. the first examples of this increasing demand are the Global Monitoring for Environment and Security -GMES or the Disaster Monitoring constellation. The increasing trend in the use of multiple platforms is opening new challenges in terms of coordination and high responsiveness principally in critical scenarios. In particular, a new concept of mission planning has been identified in order to operate such constellations of spacecraft and provide a greater level of responsiveness.In this paper, we describe an innovative ground-based automated planning & scheduling system for multiple platforms, specifically for the Disaster Monitoring Constellation. First, we show how the system can be applied to a single platform case study designed for a highly dynamic environment. The system will be required to respond appropriately to different priority levels and the needs of different user groups. Finally an outline will be given regarding the systems extension to the whole Disaster Monitoring constellation in order to show the coordination benefits of our solution.The novelty of this project is applying a natural-inspired paradigm, such as stigmergy, to coordinate a platform and compute the solution. More specifically, a novel algorithm designed for dynamic planning is applied. It offers a high-level of adaptability and responsiveness allowing the system to find near-optimum solutions on a global level thanks to the collaboration of all the agents interacting and modifying the environment. This approach is based on ant colony algorithms and aims at extending mission planning applications to face real constellation scenarios.
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