Quantao Yang
Title: Doctoral Student School/office: School of Science and TechnologyEmail: quantao.yang@oru.se
Phone: +46 19 303621
Room: T1212

Research subject
Research environments
Research projects
Active projects
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Publications
Articles in journals |
Conference papers |
Articles in journals
- Yang, Q. , Stork, J. A. & Stoyanov, T. (2022). MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer. IEEE Robotics and Automation Letters, 7 (3), 7652-7659.
- Yang, Q. , Dürr, A. , Topp, E. A. , Stork, J. A. & Stoyanov, T. (2022). Variable Impedance Skill Learning for Contact-Rich Manipulation. IEEE Robotics and Automation Letters, 7 (3), 8391-8398.
Conference papers
- Yang, Q. , Stork, J. A. & Stoyanov, T. (2022). Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation. Paper presented at 2nd RL-CONFORM Workshop at IROS 2022, October 23, 2022.
- Yang, Q. , Dürr, A. , Topp, E. A. , Stork, J. A. & Stoyanov, T. (2021). Learning Impedance Actions for Safe Reinforcement Learning in Contact-Rich Tasks. In: NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM). Paper presented at NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM), (Online conference), Sydney, Australia, December 6-14, 2021.
- Yang, Q. , Stork, J. A. & Stoyanov, T. (2021). Null space based efficient reinforcement learning with hierarchical safety constraints. In: 2021 European Conference on Mobile Robots (ECMR). Paper presented at European Conference on Mobile Robots (ECMR 2021), Virtual meeting, August 31 - September 3, 2021. IEEE.