Yuxuan Yang

Postdoc

AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T2247
Phone
yuxuan.yang@oru.se

My research interests lie in machine learning and robotics.

In particular, I am interested in improving robot manipulation performance regarding deformable objects via learning-based dynamics modeling. More specifically, I am currently working on designing a learning-based dynamics model for deformable linear objects so that a robot can manipulate the objects using model-based control methods.

Publications

Journal Articles

[1]	Y. Yang, J. A. Stork and T. Stoyanov. Learning differentiable dynamics models for shape control of deformable linear objects. Robotics and Autonomous Systems, 158, 2022 [ BibTeX \| DiVA ]
[2]	Y. Yang, J. A. Stork and T. Stoyanov. Particle Filters in Latent Space for Robust Deformable Linear Object Tracking. IEEE Robotics and Automation Letters, 7(4):12577-12584, 2022 [ BibTeX \| DiVA ]

Refereed Conference and Workshop Articles

[1]	Y. Yang, J. A. Stork and T. Stoyanov. Learn to Predict Posterior Probability in Particle Filtering for Tracking Deformable Linear Objects. In 3rd Workshop on Robotic Manipulation of Deformable Objects: Challenges in Perception, Planning and Control for Soft Interaction (ROMADO-SI), IROS 2022, Kyoto, Japan 2022 [ BibTeX \| DiVA \| PDF ]
[2]	Y. Yang, J. A. Stork and T. Stoyanov. Online Model Learning for Shape Control of Deformable Linear Objects. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4056-4062, 2022 [ BibTeX \| DiVA \| PDF ]
[3]	Y. Yang, J. A. Stork and T. Stoyanov. Learning to Propagate Interaction Effects for Modeling Deformable Linear Objects Dynamics. In 2021 IEEE International Conference on Robotics and Automation (ICRA) : IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 30 - June 5, 2021, pages 1950-1957, 2021 [ BibTeX \| DiVA \| PDF ]

Theses

[1]	Y. Yang. Advancing Modeling and Tracking of Deformable Linear Objects for Real-World Applications. Örebro University, School of Science and Technology, Ph.D. Thesis, 2023 [ BibTeX \| DiVA ]