Rita Laezza

Postdoc at Automation

Rita Laezza is a Postdoc in the Automation group. Rita has a background in Biomedical Engineering at Chalmers, having specialized in Signals and Control, and completed her thesis on Deep Learning for myoelectric pattern recognition at the Biomechatronics and Neurorehabilitation Lab. Her PhD research focused on Reinforcement Learning (RL) for robotic manipulation of deformable objects. Her goal was to deal with the manipulation of deformable objects by combining Deep Neural Networks and control policies based on RL principles. This project ran in collaboration with WASP.

Source: chalmers.se
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Showing 11 publications

2024

Offline Goal-Conditioned Reinforcement Learning for Shape Control of Deformable Linear Objects

Rita Laezza, Mohammadreza Shetab-Bushehri, Gabriel Arslan Waltersson et al
Preprint
2023

Offline Reinforcement Learning for Shape Control of Deformable Linear Objects from Limited Real Data

Rita Laezza, Mohammadreza Shetab-Bushehri, Erol Özgür et al
Other conference contribution
2022

Planning and Control for Cable-routing with Dual-arm Robot

Gabriel Arslan Waltersson, Rita Laezza, Yiannis Karayiannidis
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 2022-May, p. 1046-1052
Paper in proceeding
2022

Blind Manipulation of Deformable Linear Objects Based on Force Information from Environmental Contacts

Rita Laezza, Finn Süberkrüb, Yiannis Karayiannidis
Other conference contribution
2022

Feel the Tension: Manipulation of Deformable Linear Objects in Environments with Fixtures using Force Information

Finn Süberkrüb, Rita Laezza, Yiannis Karayiannidis
IEEE International Conference on Intelligent Robots and Systems. Vol. 2022-October, p. 11216-11222
Paper in proceeding
2021

ReForm: A Robot Learning Sandbox for Deformable Linear Object Manipulation

Rita Laezza, Robert Gieselmann, Florian T. Pokorny et al
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 2021-May, p. 4717-4723
Paper in proceeding
2021

Presenting ReForm, a Robot Learning Sandbox for Deformable Linear Object Manipulation

Rita Laezza, Robert Gieselmann, Florian T. Pokorny et al
Other conference contribution
2021

Learning Shape Control of Elastoplastic Deformable Linear Objects

Rita Laezza, Yiannis Karayiannidis
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 2021-May, p. 4438-4444
Paper in proceeding
2020

Shape Control of Elastoplastic Deformable Linear Objects through Reinforcement Learning

Rita Laezza, Yiannis Karayiannidis
Other conference contribution

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