AI x Future Combat Air System

• Multi-constraint optimization for dynamic use of heterogeneous resources

On the basis of several use cases describing:

1. a theater with actors capable of reacting and interacting
2. drivable resources, with variable capacities and their own constraints
3. a "mission" objective aiming at multi-criteria performances (accuracy, delay, coverage...) in the respect of implementation rules (constraints)

The solution should propose and evaluate planning and optimization techniques under constraints. It should be CPU efficient, improve the success rate of the mission, be modular and scalable, and if possible explainable, and/or capable of proposing alternative plans, with possible human intervention.

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• Creating solutions for learning with few examples or guided learning

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• Synthetic image production

The solution concerns the SAR/OPTRO cooperation in aerial to ground imagery, to realign the images, and improve the detection of objects of interest.
To do this, it is necessary to massively simulate optronic and SAR images corresponding to the same scenes and with the same objects in a large variability of contexts, so as to be able to train machine learning algorithms.

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• Developing solutions for incremental database enrichment with novelty integration
• Creating algorithms for change analysis
• Developing solutions for abnormal behavior detection