Dr Yanlong Huang
- Position: University Academic Fellow
- Areas of expertise: Imitation learning; Reinforcement learning.
- Email: Y.L.Huang@leeds.ac.uk
- Phone: +44(0)113 343 3505
- Location: 2.21C Sir William Henry Bragg Building
- Website: GitHub | Googlescholar | Researchgate
Profile
I am a University Academic Fellow (Assistant Professor) at the School of Computer Science.
I am an Associate Editor for
- IEEE Robotics and Automation Letters
- IEEE Transactions on Automation Science and Engineering
- Transactions of the Institute of Measurement and Control
- IEEE International Conference on Intelligent Robots and Systems (2022 - 2024)
Prospective students
I am looking for highly self-motivated and passionate PhD students who are interested in the following topics: imitation learning, deep reinforcement learning, computer vision, object detection and manipulation, task and motion planning, optimal control.
Application: send me your CV, BSc, and MSc transcripts in your enquiry email. You may visit our lab, but please make an appointment with one of my PhD students.
Selected Publications
- J. Ding, C. Santina, T. Lam, J. Pang, X. Xiao, N. Tsagarakis, and Y. Huang. Robust humanoid locomotion via sequential stepping and angular momentum optimization, IEEE Transactions on Industrial Electronics, 2024.
- J. Silvério and Y. Huang. A non-parametric skill representation with soft null space projectors for fast generalization, IEEE International Conference on Robotics and Automation (ICRA), 2023.
- P. Xu, L. Ding, Z. Li, J. Shi, H. Gao, G. Liu, and Y. Huang. A closed-loop shared control framework for legged robots, IEEE Transactions on Mechatronics (T-MECH), 2023.
- P. Xu, L. Ding, Z. Li, H. Yang, Z. Wang, H. Gao, R. Zhou, Y. Su, Z. Deng, and Y. Huang. Learning physical characteristics like animals for legged robots, National Science Review (NSR), 2023.
- J. Ding, T. Lam, L. Ge, J. Pang, and Y. Huang. Safe and adaptive 3D locomotion via constrained task space imitation learning, IEEE Transactions on Mechatronics (T-MECH), 2023.
- Y. Huang, D. Xu, and M. Tan. On imitation learning of robot movement trajectories: A survey, Acta Automatica Sinica, 2022.
- F. J. Abu-Dakka, Y. Huang, J. Silvério, and V. Kyrki. A probabilistic framework for learning geometry-based robot manipulation skills, Robotics and Autonomous Systems (RAS), 2021. [video]
- Y. Huang, F. J. Abu-Dakka, J. Silvério, and D. G. Caldwell. Towards orientation learning and adaptation in Cartesian space, IEEE Transactions on Robotics (T-RO), 2020. [page]
- J. Ding, X. Xiao, N. Tsagarakis, and Y. Huang. Robust gait synthesis combining constrained optimization and imitation learning, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
- Y. Huang and D. G. Caldwell. A linearly constrained nonparametric framework for imitation learning, IEEE International Conference on Robotics and Automation (ICRA), 2020. [video]
- J. Silvério, Y. Huang, F. J. Abu-Dakka, L. Rozo, D. G. Caldwell. Uncertainty aware imitation learning using kernelized movement primitives, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019. [video][code]
- Y. Huang, L. Rozo, J. Silvério, and D. G. Caldwell. Kernelized movement primitives, The International Journal of Robotics Research (IJRR), 2019. [video][code]
- Y. Huang, F. J. Abu-Dakka, J. Silvério, and D. G. Caldwell. Generalized orientation learning in robot task space, IEEE International Conference on Robotics and Automation (ICRA), 2019. [video][code]
- Y. Huang, L. Rozo, J. Silvério, and D. G. Caldwell. Non-parametric imitation learning of robot motor skills, IEEE International Conference on Robotics and Automation (ICRA), 2019. [code]
- Y. Huang, J. Silvério, and D. G. Caldwell. Towards minimal intervention control with competing constraints, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
- J. Silvério, Y. Huang, L. Rozo, and D. G. Caldwell. An uncertainty-aware minimal intervention control strategy learned from demonstrations, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018. [video]
- J. Silvério, Y. Huang, L. Rozo, S. Calinon, and D. G. Caldwell. Probabilistic learning of torque controllers from kinematic and force constraints, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018. [video]
- Y. Huang, J. Silvério, L. Rozo, and D. G. Caldwell. Generalized task-parameterized skill learning, IEEE International Conference on Robotics and Automation (ICRA), 2018. [video]
- Y. Huang, J. Silvério, L. Rozo, and D. G. Caldwell. Hybrid probabilistic trajectory optimization using null-space exploration, IEEE International Conference on Robotics and Automation (ICRA), 2018. [video]
- Y. Huang, D. Buchler, O. Koc, B. Scholkopf, and J. Peters. Jointly learning trajectory generation and hitting point prediction in robot table tennis, IEEE International Conference on Humanoid Robots (HUMANOIDS), 2016. [Video]
- Y. Huang, B. Scholkopf, and J. Peters. Learning optimal striking points for a ping-pong playing robot, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.
- Y. Huang, D. Xu, M. Tan, and H. Su. Adding active learning to LWR for ping-pong playing robot, IEEE Transactions on Control Systems Technology (TCST), 2013. [video]
- Y. Huang, D. Xu, M. Tan, and H. Su. Trajectory prediction of spinning ball for ping-pong player robot, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011.
Research interests
<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://eps.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>
Student education
COMP5611M Machine Learning (Module Leader)
COMP3631 Intelligent Systems and Robotics (Module Leader)
COMP3611 Machine Learning
COMP5200M MSc Project
COMP3931/3932 Individual Project
MECH 3895 Individual Project
Current postgraduate researchers
<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>Projects
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<li><a href="//phd.leeds.ac.uk/project/1633-meta-learning-from-watching-videos">Meta learning from watching videos</a></li>
<li><a href="//phd.leeds.ac.uk/project/1087-robot-skill-learning-using-deep-reinforcement-learning">Robot Skill Learning Using Deep Reinforcement Learning</a></li>
<li><a href="//phd.leeds.ac.uk/project/2151-robotic-manipulation-of-deformable-objects-by-leveraging-physical-rules">Robotic manipulation of deformable objects by leveraging physical rules</a></li>