Lianhao Yin

Research Vision

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. 

Publications

Google Scholar 

Research Highlights

Artificial Intelligence in Surgery

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.


[Paper] 

Multi-Agent 

Lechner, M., Yin, L., Seyde, T., Wang, T. H. J., Xiao, W., Hasani, R., Rountree, J., & Rus, D. (2024). Gigastep-one billion steps per second multi-agent reinforcement learning. Advances in Neural Information Processing Systems, 36.


[Paper]  [Code] 


[ICRA]Cooperative Flight Control Using Visual-Attention.mov

Human-Robotic 

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.

[Paper] 


Nonlinear control



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.


[Paper] 




Predictive control

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.

[Paper] 

Energy system

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.

[Paper]