I am Teng Xue, a PhD student at Ecole Polytechnique Federale de Lausanne (EPFL) and a research assistant at Robot Learning and Interaction Group (RLI), Idiap Research Institute, supervised by Dr. Sylvain Calinon. Before joining Idiap/EPFL, I was fortunate to work as a research intern at ETH RSL, supervised by Prof. Marco Hutter, and Stanford Artificial Intelligence Lab (SAIL), supervised by Dr. Shenli Yuan and Prof. J. Kenneth Salisbury.
I am broadly interested in planning and control for robotic systems that can physically interact with the surroundings, especially in task and motion planning and contact-rich manipulation. I am deeply interested in the underlying scientific question: How to cope with the combinatorial complexity arising from the interplay of discrete and continuous variables? To tackle this, I have investigated different tools from symbolic AI, tensor factorization, and optimal control. The proposed methods have been validated through several long-horizon dexterous manipulation tasks. Moreover, I am also interested in addressing this challenge from the learning perspective, such as learning from demonstration.
Recent News
New (2024/09) Our paper Robust Manipulation Primitive Learning via Domain Contraction is accepted to Conference on Robot Learning (CoRL), 2024!
New (2024/08) Our paper Design and Control of Roller Grasper V3 for In-Hand Manipulation is accepted to IEEE Transactions on Robotics (T-RO)!
(2024/06) Our paper Logic-Geometric Planning and Control Using Graph of Tensor Networks is accepted to RSS24 workshop: Frontiers of optimization for robotics !
(2024/06) Our paper Logic Learning from Demonstrations for Multi-step Manipulation Tasks in Dynamic Environments is accepted to RA-L!
(2024/05) Our paper Logic-Skill Programming: An Optimization-based Approach to Sequential Skill Planning is accepted to Robotics: Science and Systems (RSS), 2024!
(2024/01) Our paper D-LGP: Dynamic Logic-Geometric Program for Combined Task and Motion Planning is accepted to ICRA 2024!
(2024/01) Our paper Generalized Policy Iteration using Tensor Approximation for Hybrid Control is accepted to ICLR 2024 as spotlight (Top 5%)!
(2023/01) Our paper Demonstration-guided Optimal Control for Long-term Non-prehensile Planar Manipulation is accepted to ICRA 2023!
(2022/01) One paper about Robot Grasping in Dense Clutter is accepted to Robotics and Autonomous Systems!
(2020/05) One paper about Multimodel Fusion in pHRI is accepted to IEEE sensors journal!
(2020/02) One paper about Sequential Robot Manipulation is accepted to IEEE Access!
(2019/05) One paper about Tactile Grasping is accepted to ViTac workshop in ICRA 2019!
(2018/05) Our team, Kaibot, won the First Place in Tidy Up My Room Challenge in ICRA 2018!
(2017/02) We won the Outstanding Winner (1/8085) of MCM/ICM competition held by American Consortium for Mathematics and Its Application (COMAP). A nice collaboration with Yasheng and Taihang!