no code implementations • 29 Dec 2023 • Nisar Ahmed, Luke Burks, Kailah Cabral, Alyssa Bekai Rose
We consider the problem of evaluating dynamic consistency in discrete time probabilistic filters that approximate stochastic system state densities with Gaussian mixtures.
no code implementations • 20 Oct 2021 • Luke Burks, Hunter M. Ray, Jamison McGinley, Sousheel Vunnam, Nisar Ahmed
Autonomous robots can benefit greatly from human-provided semantic characterizations of uncertain task environments and states.
no code implementations • 22 Jul 2018 • Luke Burks, Ian Loefgren, Nisar Ahmed
This work develops novel strategies for optimal planning with semantic observations using continuous state partially observable markov decision processes (CPOMDPs).
no code implementations • 3 Jun 2018 • Luke Burks, Ian Loefgren, Luke Barbier, Jeremy Muesing, Jamison McGinley, Sousheel Vunnam, Nisar Ahmed
In search applications, autonomous unmanned vehicles must be able to efficiently reacquire and localize mobile targets that can remain out of view for long periods of time in large spaces.