Quantao Yang

Quantao Yang

PhD student

AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T1212
Phone +46 (0)19 30 36 21

LinkedInGithubGoogle Scholar

I am a doctoral student in computer science at Örebro University. My main research interests are deep reinforcement learning, sim-to-real and transfer learning. Currently I am working on robot skill learning and investigating how to apply reinforcement learning in continuous domains, such as robotic tasks. Previously, I also worked on trajectory planning, 3d perception and visual servoing.

B. Eng. in Communication Engineering, Shandong University.
M. Sc. in Information and Automation Engineering, University of Bremen.


Refereed Conference and Workshop Articles

[1] Q. Yang, A. Dürr, E. A. Topp, J. A. Stork and T. Stoyanov. Learning Impedance Actions for Safe Reinforcement Learning in Contact-Rich Tasks. In NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM) 2021BibTeX | DiVA | PDF ]
[2] Q. Yang, J. A. Stork and T. Stoyanov. Null space based efficient reinforcement learning with hierarchical safety constraints. In 2021 European Conference on Mobile Robots (ECMR) 2021BibTeX | DiVA | PDF ]