3 papers
cs.RO2024
Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations
Shamil Mamedov, A. René Geist, Jan Swevers +1
Accurately predicting deformable linear object (DLO) dynamics is challenging, especially when the task requires a model that is both human-interpretable and computationally efficie…
cs.RO2024
Driving from Vision through Differentiable Optimal Control
Flavia Sofia Acerbo, Jan Swevers, Tinne Tuytelaars +1
This paper proposes DriViDOC: a framework for Driving from Vision through Differentiable Optimal Control, and its application to learn autonomous driving controllers from human dem…
cs.RO2024
Learning deformable linear object dynamics from a single trajectory
Shamil Mamedov, A. René Geist, Ruan Viljoen +2
The manipulation of deformable linear objects (DLOs) via model-based control requires an accurate and computationally efficient dynamics model. Yet, data-driven DLO dynamics models…