collaborators

6 papers

eess.SY2026

Critical slowing down for predicting controller induced loss of control in quadrotors

Jasper J. van Beers, Prashant Solanki, Erik-Jan van Kampen +1

We develop a novel forecasting scheme to anticipate controller induced loss of control (LOC) in quadrotors and evaluate it on real LOC flight data from four different quadrotors. F…

eess.SY2026

Reachability-Preserving Bellman Operator for the Discounted Reach-Cost Value Function: Uniting Hamilton-Jacobi Reachability and Reinforcement Learning

Isabelle El-Hajj, Prashant Solanki, Jasper van Beers +2

Hamilton-Jacobi (HJ) reachability provides rigorous safety and reachability guarantees for continuous-time dynamical systems, but its numerical solution suffers from the curse of d…

eess.SY2026

From Singleton Obstacles to Clutter: Translation Invariant Compositional Avoid Sets

Prashant Solanki, Jasper Van Beers, Coen De Visser

This paper studies obstacle avoidance under translation invariant dynamics using an avoid-side travel cost Hamilton Jacobi formulation. For running costs that are zero outside an o…

eess.SY2026

Unifying Hamilton-Jacobi Reachability and Reinforcement Learning

Prashant Solanki, Isabelle El-Hajj, Jasper van Beers +2

We unify Hamilton-Jacobi (HJ) reachability and Reinforcement Learning (RL) through a proposed running cost formulation. We prove that the resultant travel-cost value function is th…

eess.SY2026

Certifying Hamilton-Jacobi Reachability Learned via Reinforcement Learning

Prashant Solanki, Isabelle El-Hajj, Jasper J. van Beers +2

We present a framework to \emph{certify} Hamilton--Jacobi (HJ) reachability learned by reinforcement learning (RL). Building on a discounted initial time \emph{travel-cost} formula…

eess.SY2025

Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets

Prashant Solanki, Nikolaus Vertovec, Yannik Schnitzer +3

Recent approaches to leveraging deep learning for computing reachable sets of continuous-time dynamical systems have gained popularity over traditional level-set methods, as they o…