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data-efficient modeling 1dynamics prediction 1lifted phase space 1real-world robotics 1symplectic learning 1

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cs.RO2026

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts

Aristotelis Papatheodorou, Pranav Vaidhyanathan, Natalia Ares +2

The paper introduces CaLiSym, a framework that learns symplectic dynamics for real-world robotic systems by embedding states and ports into a lifted phase space, enabling accurate…