Goal: Let robots learn to interact with humans and environments
Problem to Solve: I would like to solve fundamental problems to let robots to learning and interact with humans and environments, with applications in aerial robots, mobile robots, medical robots, manufacturing, energy systems, and beyond.
Yin, L., Ban, Y., Eckhoff, J., Meireles, O., Rus, D., & Rosman, G. (2024). Hypergraph-Transformer (HGT) for Interactive Event Prediction in Laparoscopic and Robotic Surgery. arXiv preprint arXiv:2402.01974.
Yin, L., Wang, T., Chahine, M., Seyde, T., Lechner, M., Hasani, R.M., & Rus, D. (2022). Towards Cooperative Flight Control Using Visual-Attention. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6334-6341.
Yin, L., Turesson, G., Tunestål, P., & Johansson, R. (2021). Sliding mode control on receding horizon: Practical control design and application. Control Engineering Practice, 109, 104724.
L. Yin, G. Turesson, P. Tunestål and R. Johansson, (2020). Model predictive control of an advanced multiple cylinder engine with partially premixed combustion concept. IEEE/ASME Transactions on Mechatronics, 25(2), 804-814.
Yin, L., Lundgren, M., Wang, Z., Stamatoglou, P., Richter, M., Andersson, Ö., & Tunestål, P. (2019). High efficient internal combustion engine using partially premixed combustion with multiple injections. Applied Energy, 233, 516-523.