Students
This research thrust addresses the development and exploration of novel data-driven stochastic modeling and statistical learning approaches for enabling intelligent self-aware fly-by-feel aerial vehicles of the future that can (i) sense their surrounding environment, operating and structural states, (ii) model and interpret heterogeneous multi-modal sensing information, (iii) determine their actual operating state and structural health condition in highly-dynamic rapidly-evolving environments, and (iv) can self-assess the correctness of state estimation methods.
