52 citations · 199 across the 66 of their papers we have counts for
36 papers · 1 filter
Safety-aware Model Predictive Path Integral Control with Signal Temporal Logic
Yiqi Zhao, Taekyung Kim, Hideki Okamoto +4
Safety-aware motion planning remains a challenge in robotics, especially when missions are time-critical and are under complex specifications. In this paper, we propose safety-awar…
FalconTrack: Photorealistic Auto-Labeled Perception and Physics-Aware Vision-Based Aerial Tracking
Yan Miao, Karteek Gandiboyina, Noah Giles +4
Vision-based aerial tracking is critical in GPS-denied environments. Reliable perception for tracking depends on large-scale labeled data, yet most photorealistic datasets rely on…
DiffCVaR: Reinforcement Learning for Risk Adaptation via Differentiable CVaR Barrier Functions
Xinyi Wang, Taekyung Kim, Bardh Hoxha +2
Planning through crowded environments under uncertain obstacle motions remains difficult, as stochastic interactions often induce overly conservative behavior or reduced efficiency…
Policy Library CBF: Finite-Horizon Safety at Runtime via Parallel Rollouts
Taekyung Kim, Hideki Okamoto, Bardh Hoxha +2
Safety-critical autonomy in unstructured environments poses significant challenges for online safety certification under evolving constraints. We propose Policy Library Control Bar…
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…
Safe Model Predictive Diffusion with Shielding
Taekyung Kim, Keyvan Majd, Hideki Okamoto +3
Generating safe, kinodynamically feasible, and optimal trajectories for complex robotic systems is a central challenge in robotics. This paper presents Safe Model Predictive Diffus…
Performance-Guided Refinement for Visual Aerial Navigation using Editable Gaussian Splatting in FalconGym 2.0
Yan Miao, Ege Yuceel, Georgios Fainekos +3
Visual policy design is crucial for aerial navigation. However, state-of-the-art visual policies often overfit to a single track and their performance degrades when track geometry…
GPU-Accelerated Barrier-Rate Guided MPPI Control for Tractor-Trailer Systems
Keyvan Majd, Hardik Parwana, Bardh Hoxha +3
Articulated vehicles such as tractor-trailers, yard trucks, and similar platforms must often reverse and maneuver in cluttered spaces where pedestrians are present. We present how…
BR-MPPI: Barrier-Rate Guided MPPI for Enforcing Multiple Inequality Constraints with Learned Signed Distance Fields
Hardik Parwana, Taekyung Kim, Kehan Long +4
Model Predictive Path Integral (MPPI) control provides a sampling-based framework for optimal control, while Control Barrier Functions (CBFs) provide a principled means of enforcin…
MRTA-Sim: A Modular Simulator for Multi-Robot Allocation, Planning, and Control in Open-World Environments
Victoria Marie Tuck, Hardik Parwana, Pei-Wei Chen +5
This paper introduces MRTA-Sim, a Python/ROS2/Gazebo simulator for testing approaches to Multi-Robot Task Allocation (MRTA) problems on simulated robots in complex, indoor environm…
Safe Navigation in Uncertain Crowded Environments Using Risk Adaptive CVaR Barrier Functions
Xinyi Wang, Taekyung Kim, Bardh Hoxha +2
Robot navigation in dynamic, crowded environments poses a significant challenge due to the inherent uncertainties in the obstacle model. In this work, we propose a risk-adaptive ap…
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…
Repairing Neural Networks for Safety in Robotic Systems using Predictive Models
Keyvan Majd, Geoffrey Clark, Georgios Fainekos +1
This paper introduces a new method for safety-aware robot learning, focusing on repairing policies using predictive models. Our method combines behavioral cloning with neural netwo…
Neural Configuration Distance Function for Continuum Robot Control
Kehan Long, Hardik Parwana, Georgios Fainekos +3
This paper presents a novel method for modeling the shape of a continuum robot as a Neural Configuration Euclidean Distance Function (N-CEDF). By learning separate distance fields…
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…
Optimal Planning for Timed Partial Order Specifications
Kandai Watanabe, Georgios Fainekos, Bardh Hoxha +3
This paper addresses the challenge of planning a sequence of tasks to be performed by multiple robots while minimizing the overall completion time subject to timing and precedence…
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…
SMT-Based Dynamic Multi-Robot Task Allocation
Victoria Marie Tuck, Pei-Wei Chen, Georgios Fainekos +4
Multi-Robot Task Allocation (MRTA) is a problem that arises in many application domains including package delivery, warehouse robotics, and healthcare. In this work, we consider th…
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…
Certifiably-correct Control Policies for Safe Learning and Adaptation in Assistive Robotics
Keyvan Majd, Geoffrey Clark, Tanmay Khandait +4
Guaranteeing safety in human-centric applications is critical in robot learning as the learned policies may demonstrate unsafe behaviors in formerly unseen scenarios. We present a…
Safe Robot Learning in Assistive Devices through Neural Network Repair
Keyvan Majd, Geoffrey Clark, Tanmay Khandait +4
Assistive robotic devices are a particularly promising field of application for neural networks (NN) due to the need for personalization and hard-to-model human-machine interaction…
NMPC-LBF: Nonlinear MPC with Learned Barrier Function for Decentralized Safe Navigation of Multiple Robots in Unknown Environments
Amir Salimi Lafmejani, Spring Berman, Georgios Fainekos
In this paper, we present a decentralized control approach based on a Nonlinear Model Predictive Control (NMPC) method that employs barrier certificates for safe navigation of mult…
Formalizing and Evaluating Requirements of Perception Systems for Automated Vehicles using Spatio-Temporal Perception Logic
Mohammad Hekmatnejad, Bardh Hoxha, Jyotirmoy V. Deshmukh +2
Automated vehicles (AV) heavily depend on robust perception systems. Current methods for evaluating vision systems focus mainly on frame-by-frame performance. Such evaluation metho…