Richard Schwarzkopf — accepted AI-conference papers

2026

M3TR: A Generalist Model for Real-World HD Map Completion

Fabian Immel, Richard Schwarzkopf, Frank Bieder, Jan-Hendrik Pauls, Christoph Stiller

ICRA 2026poster

Autonomous vehicles rely on HD maps for their operation, but offline HD maps eventually become outdated. For this reason, online HD map construction methods use live sensor data to infer map information instead. Research on real map changes shows that oftentimes entire parts of an HD map remain unch…

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2026

NaviTrace: Evaluating Embodied Navigation of Vision-Language Models

Tim Windecker, Manthan Patel, Moritz Reuss, Richard Schwarzkopf, Cesar Cadena, Rudolf Lioutikov +2

ICRA 2026poster

Vision–language models demonstrate unprecedented performance and generalization across a wide range of tasks and scenarios. Integrating these foundation models into robotic navigation systems opens pathways toward building general-purpose robots. Yet, evaluating these models’ navigation capabilities…

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