10 citations · 12 across the 19 of their papers we have counts for
19 papers
CUDA MPC: A GPU-Native Solver for Model Predictive Control
Babak Akbari, Melissa Greeff
Model Predictive Control (MPC) delivers constraint-aware control, but its reliance on online optimization limits its use on systems with fast dynamics, high-dimensional models, or…
Anisotropic Template Ansätze for Robust Positive Invariance under State-Dependent Uncertainty
Abdelrahman Ramadan, Melissa Greeff, Sidney Givigi
We establish sufficient conditions for robust positive invariance under state- and input-dependent disturbances with anisotropic covariance structure. The proposed ansatz maps a fi…
Lights Out: A Nighttime UAV Localization Framework Using Thermal Imagery and Semantic 3D Maps
Ryan Allen, Melissa Greeff
Reliable backup localization for unmanned aerial vehicles (UAVs) operating in GNSS-denied nighttime conditions remains an open challenge due to the severe modality gap between dayt…
A Lightweight Toggleable Adhesion Prototype for Multirotor UAV Landing on Tilting Platforms
Teighin Nordholt, Melissa Greeff
Autonomous multirotor landings on uncrewed surface vessels (USVs) are critical for persistent maritime operations but remain challenging due to wave-induced tilt, wind disturbances…
A Case Study in Recovery of Drones using Discrete-Event Systems
Liam P. Burns, Dayse M. Cavalcanti, Felipe G. Cabral +4
Discrete-event systems and supervisory control theory provide a rigorous framework for specifying correct-by-construction behavior. However, their practical application to swarm ro…
Impact-Aware Model Predictive Control for UAV Landing on a Heaving Platform
Jess Stephenson, Melissa Greeff
Landing UAVs on heaving marine platforms is challenging because relative vertical motion can generate large impact forces and cause rebound on touchdown. To address this, we develo…
Physics-Constrained Denoising Autoencoders for Data-Scarce Wildfire UAV Sensing
Abdelrahman Ramadan, Zahra Dorbeigi Namaghi, Emily Taylor +5
Wildfire monitoring requires high-resolution atmospheric measurements, yet low-cost sensors on Unmanned Aerial Vehicles (UAVs) exhibit baseline drift, cross-sensitivity, and respon…
UAV See, UGV Do: Aerial Imagery and Virtual Teach Enabling Zero-Shot Ground Vehicle Repeat
Desiree Fisker, Alexander Krawciw, Sven Lilge +2
This paper presents Virtual Teach and Repeat (VirT&R): an extension of the Teach and Repeat (T&R) framework that enables GPS-denied, zero-shot autonomous ground vehicle navigation…
A Time and Place to Land: Online Learning-Based Distributed MPC for Multirotor Landing on Surface Vessel in Waves
Jess Stephenson, William S. Stewart, Melissa Greeff
Landing a multirotor unmanned aerial vehicle (UAV) on an uncrewed surface vessel (USV) extends the operational range and offers recharging capabilities for maritime and limnology a…
Tiny Learning-Based MPC for Multirotors: Solver-Aware Learning for Efficient Embedded Predictive Control
Babak Akbari, Justin Frank, Melissa Greeff
Tiny aerial robots hold great promise for applications such as environmental monitoring and search-and-rescue, yet face significant control challenges due to limited onboard comput…
Distributed Model Predictive Control for Cooperative Multirotor Landing on Uncrewed Surface Vessel in Waves
Jess Stephenson, Nathan T. Duncan, Melissa Greeff
Heterogeneous autonomous robot teams consisting of multirotor and uncrewed surface vessels (USVs) have the potential to enable various maritime applications, including advanced sea…
A Computationally Efficient Learning-Based Model Predictive Control for Multirotors under Aerodynamic Disturbances
Babak Akbari, Melissa Greeff
Neglecting complex aerodynamic effects hinders high-speed yet high-precision multirotor autonomy. In this paper, we present a computationally efficient learning-based model predict…
A Remote Sim2real Aerial Competition: Fostering Reproducibility and Solutions' Diversity in Robotics Challenges
Spencer Teetaert, Wenda Zhao, Niu Xinyuan +21
Shared benchmark problems have historically been a fundamental driver of progress for scientific communities. In the context of academic conferences, competitions offer the opportu…
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety Filter
Adam W. Hall, Melissa Greeff, Angela P. Schoellig
Learning-based optimal control algorithms control unknown systems using past trajectory data and a learned model of the system dynamics. These controllers use either a linear appro…
Fly Out The Window: Exploiting Discrete-Time Flatness for Fast Vision-Based Multirotor Flight
Melissa Greeff, Siqi Zhou, Angela P. Schoellig
Current control design for fast vision-based flight tends to rely on high-rate, high-dimensional and perfect state estimation. This is challenging in real-world environments due to…
safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics
Zhaocong Yuan, Adam W. Hall, Siqi Zhou +4
In recent years, both reinforcement learning and learning-based control -- as well as the study of their safety, which is crucial for deployment in real-world robots -- have gained…
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
Lukas Brunke, Melissa Greeff, Adam W. Hall +4
The last half-decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learni…
There's No Place Like Home: Visual Teach and Repeat for Emergency Return of Multirotor UAVs During GPS Failure
Michael Warren, Melissa Greeff, Bhavit Patel +3
Redundant navigation systems are critical for safe operation of UAVs in high-risk environments. Since most commercial UAVs almost wholly rely on GPS, jamming, interference and mult…
Model Predictive Path-Following for Constrained Differentially Flat Systems
Melissa Greeff, Angela P. Schoellig
For many tasks, predictive path-following control can significantly improve the performance and robustness of autonomous robots over traditional trajectory tracking control. It doe…