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Ph.D. Dissertation Defense - Sarai Sherfield

Title:  Real-Time Mobility Estimation For Autonomous Rotorcraft To Support Long-Term Autonomy

Committee:

Dr. Mark Costello, AE, Chair, Advisor

Dr. Samuel Coogan, ECE, Co-Advisor

Dr. Jonathan Rogers, AE

Dr. Bonnie Ferri, ECE

Dr. Matthew Hale, ECE

Dr. Anirban Mazumdar, ME

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Summary

This thesis explores real-time mobility estimation 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 bounds. Continuous estimation of the performance envelope of an air vehicle is a necessary element for long-term autonomy of air vehicles to ensure survivability.

Details

Thursday
Dec 7 2023
01:00pm - 03:00pm

Location: Room 4222, Library

In campus calendar: No

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Status

  • Workflow status: Published
  • Created by: Daniela Staiculescu
  • Created: 11/30/2023
  • Modified By: Daniela Staiculescu
  • Modified: 11/30/2023

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