activity
20182023
most citedAsynchronous Blob Tracker for Event Cameras

20 citations · 52 across the 15 of their papers we have counts for

collaborators

16 papers

cs.CV2023★ 20 cited

Asynchronous Blob Tracker for Event Cameras

Ziwei Wang, Timothy Molloy, Pieter van Goor +1

Event-based cameras are popular for tracking fast-moving objects due to their high temporal resolution, low latency, and high dynamic range. In this paper, we propose a novel algor…

math.OC2023

Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking: Extended Version

Yitian Chen, Timothy L. Molloy, Tyler Summers +1

In this paper, we propose and analyze a new method for online linear quadratic regulator (LQR) control with a priori unknown time-varying cost matrices. The cost matrices are revea…

eess.SY2022

Minimum-Time Escape from a Circular Region for a Dubins Car

Timothy L. Molloy, Iman Shames

We investigate the problem of finding paths that enable a robot modeled as a Dubins car (i.e., a constant-speed finite-turn-rate unicycle) to escape from a circular region of space…

eess.SY2021★ 6 cited

Entropy-Regularized Partially Observed Markov Decision Processes

Timothy L. Molloy, Girish N. Nair

We investigate partially observed Markov decision processes (POMDPs) with cost functions regularized by entropy terms describing state, observation, and control uncertainty. Standa…

eess.SY2021★ 13 cited

Smoother Entropy for Active State Trajectory Estimation and Obfuscation in POMDPs

Timothy L. Molloy, Girish N. Nair

We study the problem of controlling a partially observed Markov decision process (POMDP) to either aid or hinder the estimation of its state trajectory. We encode the estimation ob…

eess.SY2021

Active Trajectory Estimation for Partially Observed Markov Decision Processes via Conditional Entropy

Timothy L. Molloy, Girish N. Nair

In this paper, we consider the problem of controlling a partially observed Markov decision process (POMDP) in order to actively estimate its state trajectory over a fixed horizon w…

eess.SY2021

Smoothing-Averse Control: Covertness and Privacy from Smoothers

Timothy L. Molloy, Girish N. Nair

In this paper we investigate the problem of controlling a partially observed stochastic dynamical system such that its state is difficult to infer using a (fixed-interval) Bayesian…

cs.CV2020★ 13 cited

Intelligent Reference Curation for Visual Place Recognition via Bayesian Selective Fusion

Timothy L. Molloy, Tobias Fischer, Michael Milford +1

A key challenge in visual place recognition (VPR) is recognizing places despite drastic visual appearance changes due to factors such as time of day, season, weather or lighting co…

eess.SY2020

Exactly Optimal Bayesian Quickest Change Detection for Hidden Markov Models

Jason J. Ford, Jasmin James, Timothy L. Molloy

This paper considers the quickest detection problem for hidden Markov models (HMMs) in a Bayesian setting. We construct an augmented HMM representation of the problem that allows t…

eess.SY2020

Online Inverse Optimal Control for Control-Constrained Discrete-Time Systems on Finite and Infinite Horizons

Timothy L. Molloy, Jason J. Ford, Tristan Perez

In this paper, we consider the problem of computing parameters of an objective function for a discrete-time optimal control problem from state and control trajectories with active…

eess.SY2020

Misspecified and Asymptotically Minimax Robust Quickest Change Diagnosis

Timothy L. Molloy

The problem of quickly diagnosing an unknown change in a stochastic process is studied. We establish novel bounds on the performance of misspecified diagnosis algorithms designed f…

eess.SY2020

An Optimal Bearing-Only-Information Strategy for Unmanned Aircraft Collision Avoidance

Timothy L. Molloy, Tristan Perez, Brendan P. Williams

This paper presents a novel collision avoidance strategy for unmanned aircraft detect and avoid that requires only information about the relative bearing angle between an aircraft…

cs.RO2019

Below Horizon Aircraft Detection Using Deep Learning for Vision-Based Sense and Avoid

Jasmin James, Jason J. Ford, Timothy L. Molloy

Commercial operation of unmanned aerial vehicles (UAVs) would benefit from an onboard ability to sense and avoid (SAA) potential mid-air collision threats. In this paper we present…

eess.SY2019

On the Informativeness of Measurements in Shiryaev's Bayesian Quickest Change Detection

Jason J. Ford, Jasmin James, Timothy L. Molloy

This paper provides the first description of a weak practical super-martingale phenomenon that can emerge in the test statistic in Shiryaev's Bayesian quickest change detection (QC…

eess.SY2019

A Novel Technique for Rejecting Non-Aircraft Artefacts in Above Horizon Vision-Based Aircraft Detection

Jasmin James, Jason J. Ford, Timothy L. Molloy

Unmanned aerial vehicle (UAV) operations are steadily expanding into many important applications. A key technology for better enabling their commercial use is an onboard sense and…

eess.SY2018

Quickest Detection of Intermittent Signals With Application to Vision Based Aircraft Detection

Jasmin James, Jason J. Ford, Timothy L. Molloy

In this paper we consider the problem of quickly detecting changes in an intermittent signal that can (repeatedly) switch between a normal and an anomalous state. We pose this inte…