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Learning Forced Multibody Dynamics on Lie Groups

Year: 2026

Type: preprint

Abstract: We propose an architecture for learning the dynamics of mechanical systems based on discrete forced Euler-Lagrange equations on Lie groups using only position data. By formulating the dynamics directly on manifold-valued configuration spaces, the method naturally respects the geometric structure of the systems and preserves geometric invariants and conservation laws. The reliance on position measurements alone makes the framework applicable in settings where velocity data are unavailable or noisy. The approach extends naturally to multibody systems, accommodates external control inputs, and demonstrates strong performance on both synthetic and real-world datasets.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2607.12627

Authors: Hansen, Martine Dyring, Ghirardelli, Marta, Celledoni, Elena, de Diego, David Martin, Owren, Brynjulf

Institutions: SINTEF, Norwegian University of Science and Technology, SINTEF Digital

Topic: Dynamics and Control of Mechanical Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7168405944

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