I am a senior undergraduate student in Department of Automation at Tsinghua University. My research interests lie in robotics manipulation, human-robot interaction, and the intersection of control theory and machine learning. I was fortunate to be advised by Prof. Xiang Li and Prof. Mingguo Zhao during my undergraduate studies, and I joined the Stanford Vision and Learning Lab (SVL) as a summer research intern in 2025. In the future, I will pursue my Ph.D. at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University, under the supervision of Prof. Mengdi Xu.
Present UltraDP, a Diffusion-Policy-based method that receives multi-sensory inputs (ultrasound images, wrist camera image, contact wrench, and probe pose) and generates actions that are fit for multi-modal action distributions in autonomous ultrasound scanning. UltraDP achieves a 95% success rate in transverse scanning on previously unseen subjects, demonstrating its effectiveness.
Whole-Body Model Predictive Control for Mobile Manipulation with Task Priority Transition
Yushi Wang, Ruoqu Chen, and Mingguo Zhao
In 2025 IEEE International Conference on Robotics and Automation (ICRA), 2025
Developed a Whole-Body Model Predictive Control (WBMPC) framework to manage task priorities and scheduling in multi-task mobile manipulation scenarios. Integrated task priorities into a unified weight matrix, enabling smooth transitions across tasks in both spatial and temporal dimensions.
