Learning Deformable Linear Object Dynamics From a Single Trajectory

The dynamic manipulation of deformable objects poses a significant challenge in robotics. While model-based approaches for controlling such objects hold significant potential, their effectiveness hinges on the availability of an accurate and computationally efficient dynamics model. This work focuse...

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Veröffentlicht in:	IEEE robotics and automation letters Jg. 10; H. 7; S. 7635 - 7642
Hauptverfasser:	Mamedov, Shamil, Geist, A. Rene, Viljoen, Ruan, Trimpe, Sebastian, Swevers, Jan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.07.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	and learning for soft robots Computational modeling control Deformable models Deformation Discretization Dynamics flexible robotics Formability Heuristic algorithms Kinematics Learning Mathematical models Model learning for control modeling Neural networks Numerical models Physical properties Predictive models Rigid structures Robotics Robots
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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