7 citations · 9 across the 9 of their papers we have counts for
9 papers
Spatio-Temporal Grounding of Large Language Models from Perception Streams
Jacob Anderson, Bardh Hoxha, Georgios Fainekos +2
Embodied-AI agents must reason about how objects move and interact in 3-D space over time, yet existing smaller frontier Large Language Models (LLMs) still mis-handle fine-grained…
Risk-aware MPPI for Stochastic Hybrid Systems
Hardik Parwana, Mitchell Black, Bardh Hoxha +4
Path Planning for stochastic hybrid systems presents a unique challenge of predicting distributions of future states subject to a state-dependent dynamics switching function. In th…
Querying Perception Streams with Spatial Regular Expressions
Jacob Anderson, Georgios Fainekos, Bardh Hoxha +2
Perception in fields like robotics, manufacturing, and data analysis generates large volumes of temporal and spatial data to effectively capture their environments. However, sortin…
From Dashcam Videos to Driving Simulations: Stress Testing Automated Vehicles against Rare Events
Yan Miao, Georgios Fainekos, Bardh Hoxha +3
Testing Automated Driving Systems (ADS) in simulation with realistic driving scenarios is important for verifying their performance. However, converting real-world driving videos i…
Model Predictive Path Integral Methods with Reach-Avoid Tasks and Control Barrier Functions
Hardik Parwana, Mitchell Black, Georgios Fainekos +3
The rapid advancement of robotics necessitates robust tools for developing and testing safe control architectures in dynamic and uncertain environments. Ensuring safety and reliabi…
CBFKIT: A Control Barrier Function Toolbox for Robotics Applications
Mitchell Black, Georgios Fainekos, Bardh Hoxha +2
This paper introduces CBFKit, a Python/ROS toolbox for safe robotics planning and control under uncertainty. The toolbox provides a general framework for designing control barrier…
Scaling Learning based Policy Optimization for Temporal Logic Tasks by Controller Network Dropout
Navid Hashemi, Bardh Hoxha, Danil Prokhorov +2
This paper introduces a model-based approach for training feedback controllers for an autonomous agent operating in a highly nonlinear (albeit deterministic) environment. We desire…
Feasible Space Monitoring for Multiple Control Barrier Functions with application to Large Scale Indoor Navigation
Hardik Parwana, Mitchell Black, Bardh Hoxha +4
Quadratic programs (QP) subject to multiple time-dependent control barrier function (CBF) based constraints have been used to design safety-critical controllers. However, ensuring…
The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning
Alexander Bastounis, Alexander N. Gorban, Anders C. Hansen +5
In this work, we assess the theoretical limitations of determining guaranteed stability and accuracy of neural networks in classification tasks. We consider classical distribution-…