Learning Visual Feedback Control for Dynamic Cloth Folding

Author:

Hietala Julius1,Blanco-Mulero David1,Alcan Gokhan1,Kyrki Ville1

Affiliation:

1. Aalto University,Intelligent Robotics Group,Department of Electrical Engineering and Automation (EEA),Espoo,Finland,02150

Funder

Academy of Finland

Publisher

IEEE

Reference35 articles.

1. Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task;james;Proceedings of the 1st Annual Conference on Robot Learning ser Proceedings of Machine Learning Research,0

2. Pytorch: An imperative style, high-performance deep learning library;paszke;Advances in neural information processing systems,2019

3. Domain randomization for transferring deep neural networks from simulation to the real world

4. Does the markov decision process fit the data: testing for the markov property in sequential decision making;shi;International Conference on Machine Learning,0

5. Learning arbitrary-goal fabric folding with one hour of real robot experience;lee;Proceedings of the 2020 Conference on Robot Learning ser Proceedings of Machine Learning Research,0

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1. Model Predictive Control for Dynamic Cloth Manipulation: Parameter Learning and Experimental Validation;IEEE Transactions on Control Systems Technology;2024-07

2. A Learning-based Control Framework for Fast and Accurate Manipulation of a Flexible Object;Journal of Bionic Engineering;2024-05-21

3. Achieving Autonomous Cloth Manipulation with Optimal Control via Differentiable Physics-Aware Regularization and Safety Constraints;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Attention-Based Cloth Manipulation from Model-free Topological Representation;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. Learning Fabric Manipulation in the Real World with Human Videos;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

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