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Author

Wolfgang Hönig

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Preprint Sep 2026

DynoFluxBench: Benchmarking Kinodynamic Space-Time Planners in Dynamic Environments

Robots that leave structured, static environments must plan motions that are kinodynamically feasible and safe among moving obstacles. However, there are no dedicated benchmark frameworks that combine both aspects. To overcome this, we present DynoFluxBench, a framework to compare kinodynamic planners in known, dynamic...

Franz Queißner, Andreas Orthey, Wolfgang Hönig · 0 citations
#machine learning Preprint Sep 2026

VertexCBF: Improving Neural Control Barrier Functions via Vertex-Restricted Control Search

This paper approximate the stationary Hamilton--Jacobi value function using a neural network trained via a combination of physics-informed and sparsely supervised learning and proposes VertexCBF, a framework for learning neural CBFs in a scalable, systematic, and explainable way.

Bojan Derajić, Sebastian Bernhard, Wolfgang Hönig · 0 citations

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