Symplectic physics-embedded learning via Lie groups Hamiltonian formulation for serial manipulator dynamics prediction
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DOI: 10.1038/s41598-025-17935-w
Abstract: Accurate dynamic modeling is critical for advanced robotic control, yet conventional methods struggle with manipulator nonlinear complexity. While Hamiltonian neural networks leveraging Lie group symmetries improve physical consistency of the network, existing methods overlook key… read more here.
Keywords: symplectic physics; manipulator; lie; physics embedded ... See more keywords