7 citations · 8 across the 6 of their papers we have counts for
7 papers
PRREACH: Probabilistic Risk Assessment Using Reachability for UAV Control
Nicole Fronda, Hariharan Narayanan, Sadia Afrin Ananna +2
We present a new approach for designing risk-bounded controllers for Uncrewed Aerial Vehicles (UAVs). Existing frameworks for assessing risk of UAV operations rely on knowing the c…
FiReFly: Fair Distributed Receding Horizon Planning for Multiple UAVs
Nicole Fronda, Bardh Hoxha, Houssam Abbas
We propose injecting notions of fairness into multi-robot motion planning. When robots have competing interests, it is important to optimize for some kind of fairness in their usag…
Fair-CoPlan: Negotiated Flight Planning with Fair Deconfliction for Urban Air Mobility
Nicole Fronda, Phil Smith, Bardh Hoxha +2
Urban Air Mobility (UAM) is an emerging transportation paradigm in which Uncrewed Aerial Systems (UAS) autonomously transport passengers and goods in cities. The UAS have different…
Differentiable Inference of Temporal Logic Formulas
Nicole Fronda, Houssam Abbas
We demonstrate the first Recurrent Neural Network architecture for learning Signal Temporal Logic formulas, and present the first systematic comparison of formula inference methods…
Resilience in multi-robot multi-target tracking with unknown number of targets through reconfiguration
Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme
We address the problem of maintaining resource availability in a networked multi-robot team performing distributed tracking of unknown number of targets in an environment of intere…
Resilience in multi-robot target tracking through reconfiguration
Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme
We address the problem of maintaining resource availability in a networked multi-robot system performing distributed target tracking. In our model, robots are equipped with sensing…
Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock
Nicole Fronda, Jessica Asencio, Cameron Carlin +4
Objective: Predict individual septic children's personalized physiologic responses to vasoactive titrations by training a Recurrent Neural Network (RNN) using EMR data. Materials a…