Title:
Navigating in the Presence of Uncertainty: Why we love Bayes’ Rule
Abstract:
Accurate state estimation is essential for challenging guidance tasks such as lunar landing, submarine-launched rockets, and UAV navigation in cluttered environments. These problems require handling significant uncertainties arising from sensor noise, unmodeled dynamics, and variable environmental conditions. This talk explores how Bayesian estimation techniques, ranging from Kalman filtering to more advanced nonlinear methods, enable robust Guidance, Navigation, and Control (GN&C) solutions in such
scenarios. We will examine several real-world applications, discuss the modeling and computational considerations involved, and highlight lessons learned from Draper’s long history in GN&C system development.
Speaker:
Michael McManus
Charles Stark Draper Laboratory
Bio:
Michael McManus is the Group Lead of the APNT and Tracking Group at the Charles Stark Draper Laboratory. Michael’s career-to-date, spanning 17+ years, has focused on developing advanced estimation algorithms and software for a variety of applications in both the Aerospace and Healthcare industries. Michael has worked at Draper for over 4 years. He spent 12 years working at a healthcare startup called Etiometry, where he led the team that developed the company’s FDA[1]cleared patient tracking algorithms. Michael started his career in the Advanced Algorithms group at Lockheed Martin Missiles and Fire Control in Orlando, FL after receiving his Bachelor of Science degree in Aerospace Engineering from Boston University.
Host: Professor Alex Wyglinski