31 citations · 85 across the 19 of their papers we have counts for
23 papers
Temporally Robust Multi-Agent STL Motion Planning in Continuous Time
Joris Verhagen, Lars Lindemann, Jana Tumova
Signal Temporal Logic (STL) is a formal language over continuous-time signals (such as trajectories of a multi-agent system) that allows for the specification of complex spatial an…
Belief Control Barrier Functions for Risk-aware Control
Matti Vahs, Christian Pek, Jana Tumova
Ensuring safety in real-world robotic systems is often challenging due to unmodeled disturbances and noisy sensor measurements. To account for such stochastic uncertainties, many r…
Risk-Aware Motion Planning in Partially Known Environments
Fernando S. Barbosa, Bruno Lacerda, Paul Duckworth +2
Recent trends envisage robots being deployed in areas deemed dangerous to humans, such as buildings with gas and radiation leaks. In such situations, the model of the underlying ha…
Provably Safe Control of Lagrangian Systems in Obstacle-Scattered Environments
Fernando S. Barbosa, Lars Lindemann, Dimos V. Dimarogonas +1
We propose a hybrid feedback control law that guarantees both safety and asymptotic stability for a class of Lagrangian systems in environments with obstacles. Rather than performi…
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes
Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer
Autonomous systems are often required to operate in partially observable environments. They must reliably execute a specified objective even with incomplete information about the s…
Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving
Maxime Bouton, Jesper Karlsson, Alireza Nakhaei +3
Designing reliable decision strategies for autonomous urban driving is challenging. Reinforcement learning (RL) has been used to automatically derive suitable behavior in uncertain…