no code implementations • 4 Jul 2023 • Helen Carson, Jason J. Ford, Michael Milford
While substantial progress has been made in the absolute performance of localization and Visual Place Recognition (VPR) techniques, it is becoming increasingly clear from translating these systems into applications that other capabilities like integrity and predictability are just as important, especially for safety- or operationally-critical autonomous systems.
no code implementations • 24 Mar 2023 • Jason J. Ford, Justin M. Kennedy, Caitlin Tompkins, Jasmin James, Aaron McFadyen
This paper establishes that an exactly optimal rule for Bayesian Quickest Change Detection (QCD) of Markov chains is a threshold test on the no change posterior.
no code implementations • 16 Dec 2022 • Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo, Falko Dressler
Aiming to achieve a reliable state estimate for a legitimate estimator while ensuring secrecy, we propose a secrecy encoding scheme without the need for packet receipt acknowledgments.
no code implementations • 18 Jul 2022 • Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo
For geographically separated cyber-physical systems, state estimation at a remote monitoring or control site is important to ensure stability and reliability of the system.
no code implementations • 6 Dec 2021 • Jasmin Martin, Jenna Riseley, Jason J. Ford
The emerging global market for unmanned aerial vehicle (UAV) services is anticipated to reach USD 58. 4 billion by 2026, spurring significant efforts to safely integrate routine UAV operations into the national airspace in a manner that they do not compromise the existing safety levels.
no code implementations • 31 Aug 2020 • Jason J. Ford, Jasmin James, Timothy L. Molloy
This paper considers the quickest detection problem for hidden Markov models (HMMs) in a Bayesian setting.