39 citations · 63 across the 21 of their papers we have counts for
25 papers
Auditable and Deployable Multi-Agent Motion Planning via Posetal Games from Legal Guidelines
Florian Lercher, Karan Mahesh, Yujun Huang +6
When robots are deployed in the real-world, they must interact with other agents and accomplish their own goals while adhering to legal constraints. These potentially conflicting o…
Expressiveness, Equivalence, and Uncertainty in Velocity Obstacles and Closest Point of Approach Metrics
Elizabeth Dietrich, Liam M. Imagawa, Hanna Krasowski +3
Time to Closest Point of Approach (TCPA), Distance to Closest Point of Approach (DCPA), and Velocity Obstacles (VOs), are widely used to assess and mitigate collision risk in auton…
Decentralized Safe Multi-Agent Reinforcement Learning via Predictive Shielding
Yacine El Yamani, Hanna Krasowski, Elena Vanneaux
Environments are increasingly populated by multiple robots performing independent tasks with limited prior knowledge of each other. Deploying such multi-agent systems presents sign…
Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study
Elizabeth Dietrich, Hanna Krasowski, Emir Cem Gezer +3
Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty remains challenging, as exi…
Learning-enabled Parameter Synthesis for Nonlinear Systems from Signal Temporal Logic
Alex Beaudin, Hanna Krasowski, Eric Palanques-Tost +2
Signal Temporal Logic (STL) is increasingly used to describe interpretable objectives and constraints for optimal control and learning methods, especially when no target time serie…
X-Safe: Embodiment-Agnostic Safeguarding for Robot Arm Manipulation Policies via Action Masking
Alex Beaudin, Hanna Krasowski, Kartik Nagpal +3
Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. For collision avoidance, existing appro…
Finite-Step Invariant Sets for Hybrid Systems with Probabilistic Guarantees
Varun Madabushi, Elizabeth Dietrich, Hanna Krasowski +1
Poincare return maps are a fundamental tool for analyzing periodic orbits in hybrid dynamical systems, including legged locomotion, power electronics, and other cyber-physical syst…
Probably Approximately Correct Guarantees for Data-Driven Reachability Analysis: A Theoretical and Empirical Comparison
Elizabeth Dietrich, Hanna Krasowski, Murat Arcak
Reachability analysis evaluates system safety by identifying the set in which states may evolve over a time horizon. Data-driven reachability analysis estimates reachable sets and…
Importance Sampling for Statistical Certification of Viable Initial Sets
Elizabeth Dietrich, Hanna Krasowski, Vegard Flovik +1
We study the problem of statistically certifying viable initial sets (VISs)---sets of initial conditions whose trajectories satisfy a given control specification. While VISs can be…
Predictive Safety Shield for Dyna-Q Reinforcement Learning
Jin Pin, Krasowski Hanna, Vanneaux Elena
Obtaining safety guarantees for reinforcement learning is a major challenge to achieve applicability for real-world tasks. Safety shields extend standard reinforcement learning and…
Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning
Beyazit Yalcinkaya, Marcell Vazquez-Chanlatte, Ameesh Shah +2
We study learning multi-task, multi-agent policies for cooperative, temporal objectives, under centralized training, decentralized execution. In this setting, using automata to rep…
pacSTL: PAC-Bounded Signal Temporal Logic from Data-Driven Reachability Analysis
Hanna Krasowski, Elizabeth Dietrich, Emir Cem Gezer +3
Signal Temporal Logic (STL) is an expressive language for specifying behaviors of dynamical systems from continuous signals. However, a limitation of standard STL is its inherently…
Falsification-driven reinforcement learning for maritime motion planning
Marlon Müller, Florian Finkeldei, Hanna Krasowski +2
Compliance with maritime traffic rules is essential for the safe operation of autonomous vessels, yet training reinforcement learning (RL) agents to adhere to them is challenging.…
STL-based Optimization of Biomolecular Neural Networks for Regression and Control
Eric Palanques-Tost, Hanna Krasowski, Murat Arcak +2
Biomolecular Neural Networks (BNNs), artificial neural networks with biologically synthesizable architectures, achieve universal function approximation capabilities beyond simple b…
Safe Reinforcement Learning using Action Projection: Safeguard the Policy or the Environment?
Hannah Markgraf, Shambhuraj Sawant, Hanna Krasowski +3
Projection-based safety filters, which modify unsafe actions by mapping them to the closest safe alternative, are widely used to enforce safety constraints in reinforcement learnin…
Learning to Drive by Imitating Surrounding Vehicles
Yasin Sonmez, Hanna Krasowski, Murat Arcak
Imitation learning is a promising approach for training autonomous vehicles (AV) to navigate complex traffic environments by mimicking expert driver behaviors. While existing imita…
Intelligent Sailing Model for Open Sea Navigation
Hanna Krasowski, Stefan Schärdinger, Murat Arcak +1
Autonomous vessels potentially enhance safety and reliability of seaborne trade. To facilitate the development of autonomous vessels, simulations are required to model realistic in…
Learning Biomolecular Models using Signal Temporal Logic
Hanna Krasowski, Eric Palanques-Tost, Calin Belta +1
Modeling dynamical biological systems is key for understanding, predicting, and controlling complex biological behaviors. Traditional methods for identifying governing equations, s…
Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking
Roland Stolz, Hanna Krasowski, Jakob Thumm +3
Continuous action spaces in reinforcement learning (RL) are commonly defined as multidimensional intervals. While intervals usually reflect the action boundaries for tasks well, th…
Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea
Hanna Krasowski, Matthias Althoff
For safe operation, autonomous vehicles have to obey traffic rules that are set forth in legal documents formulated in natural language. Temporal logic is a suitable concept to for…
Stranding Risk for Underactuated Vessels in Complex Ocean Currents: Analysis and Controllers
Andreas Doering, Marius Wiggert, Hanna Krasowski +3
Low-propulsion vessels can take advantage of powerful ocean currents to navigate towards a destination. Recent results demonstrated that vessels can reach their destination with hi…
Maximizing Seaweed Growth on Autonomous Farms: A Dynamic Programming Approach for Underactuated Systems Navigating on Uncertain Ocean Currents
Matthias Killer, Marius Wiggert, Hanna Krasowski +3
Seaweed biomass presents a substantial opportunity for climate mitigation, yet to realize its potential, farming must be expanded to the vast open oceans. However, in the open ocea…
Safe Reinforcement Learning with Probabilistic Guarantees Satisfying Temporal Logic Specifications in Continuous Action Spaces
Hanna Krasowski, Prithvi Akella, Aaron D. Ames +1
Vanilla Reinforcement Learning (RL) can efficiently solve complex tasks but does not provide any guarantees on system behavior. To bridge this gap, we propose a three-step safe RL…
Provably Safe Reinforcement Learning via Action Projection using Reachability Analysis and Polynomial Zonotopes
Niklas Kochdumper, Hanna Krasowski, Xiao Wang +2
While reinforcement learning produces very promising results for many applications, its main disadvantage is the lack of safety guarantees, which prevents its use in safety-critica…