Title: Real-time Mobility Estimation for Autonomous Aerial Vehicles To Support Long-Term Autonomy
Dr. Costello, Advisor
Dr. Coogan, Co-Advisor
Dr. Rogers, Chair
Abstract: The objective of the proposed research is to design a real-time mobility estimation algorithm for autonomous air vehicles using online machine learning. The kernel of the proposed algorithm is online estimation of the total power required and total power available as a function of airspeed. Applying a sparse gaussian process to estimate the power required at various speeds presents an opportunity to exploit the relationship to assess the utility with the addition of confidence intervals. From this core estimate, all key mobility characteristics can be computed in real-time including uncertainty estimates. Continuous estimation of the performance envelope of an air vehicle is a necessary element for long-term autonomy of air vehicles to ensure survivability.