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20242026
most citedOptimal Potential Shaping on SE(3) via Neural ODEs on Lie Groups

4 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2026

Physical Human-Robot Interaction: A Critical Review of Safety Constraints

Riccardo Zanella, Federico Califano, Stefano Stramigioli

This paper aims to provide a clear and rigorous understanding of commonly recognized safety constraints in physical human-robot interaction, particularly regarding ISO/TS 15066. We…

math.NA2025

Model order reduction via Lie groups

Yannik P. Wotte, Patrick Buchfink, Silke Glas +2

Lie groups and their actions are ubiquitous in the description of physical systems, and we explore implications in the setting of model order reduction (MOR). We present a novel fr…

math.DS2025

Symmetric Lyapunov Subcenter Manifolds for Periodic Regulation of Mechanical Systems

Yannik P. Wotte, Arne Sachtler, Alin Albu-Schäffer +2

Multi-body mechanical systems have rich internal dynamics, whose solutions can be exploited as energy-efficient control targets. Yet, solutions non-trivially depend on system param…

eess.SY2024

Lossless optimal transient control for rigid bodies in 3D space

Riccardo Zanella, Federico Califano, Antonio Franchi +1

In this letter, we propose a control scheme for rigid bodies designed to optimise transient behaviors. The search space for the optimal control input is parameterized to yield a pa…

eess.SY2024

The effect of control barrier functions on energy transfers in controlled physical systems

Federico Califano, Riccardo Zanella, Alessandro Macchelli +1

Using a port-Hamiltonian formalism, we show the qualitative and quantitative effect of safety-critical control implemented with control barrier functions (CBFs) on the power balanc…

math.OC2024★ 4 cited

Optimal Potential Shaping on SE(3) via Neural ODEs on Lie Groups

Yannik P. Wotte, Federico Califano, Stefano Stramigioli

This work presents a novel approach for the optimization of dynamic systems on finite-dimensional Lie groups. We rephrase dynamic systems as so-called neural ordinary differential…