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]	D. Cáceres Domínguez, M. Iannotta, A. Kashyap, S. Sun, Y. Yang, C. Cella, M. Colombo, M. Pelosi, G. F. Preziosa, A. Tafuro, I. Zappa, F. Busch, Y. Dong, A. Longhini, H. Lu, R. I. Cabral Muchacho, J. Styrud, S. Fregnan, M. Guberina, Z. Jia, G. Carriero, S. Lindqvist, S. Di Castro and M. Iovino. The First WARA Robotics Mobile Manipulation Challenge - Lessons Learned. In 2025 European Conference on Mobile Robots (ECMR) 2025 [ BibTeX \| DiVA ]
[2]	Y. Yang, J. A. Stork and T. Stoyanov. Tracking Branched Deformable Linear Objects Using Particle Filtering on Depth Images. In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pages 912-919, 2024 [ BibTeX \| DiVA \| PDF ]
[3]	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 ]
[4]	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 ]
[5]	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 ]