Fuzzy Jump Model for Asteroids Co-orbital Regimes Identification

This work presents an extension of the statistical jump model that incorporates uncertainty estimation in cluster assignments. Leveraging the similarities between statistical jump models and the fuzzy cmeans framework, our fuzzy jump model sequentially estimates timevarying state probabilities. Our approach offers high flexibility, enabling clustering of mixed-type data. We apply it to the identification of coorbital dynamics in the three-body problem, a novel application within the machine learning framework, yet highly relevant for understanding asteroid behavior and designing trajectories for interplanetary missions.