Jiangfan Yu

Jiangfan Yu's research focuses on endowing microrobots with high levels of autonomy, intelligent decision-making capabilities, and high-efficacy medical functions. His work enables dynamic planning of optimal pathways in vivo and real-time image-guided navigation of microrobots for tasks such as minimally invasive surgery and precise diagnostics.

The hydrogel microrobot swarms he developed can efficiently maneuver and adaptively reconfigure within complex bronchial environments. Combined with a path planning method guided by medical imaging feedbacks, precise 3D localization and in vivo navigation of the microrobot swarms have been achieved for targeted drug delivery, which accelerates the clinical translation of customized lung therapies with high precision.

To address the limitations of conventional angiography, he developed magnetically controlled microrobot swarms that penetrate deep into vascular networks under magnetic guidance. They can cover regions inaccessible to traditional methods and generate precise and complete fluoroscopic images of 3D vascular structures. This technique not only improves the precision for angiography, but also lays the foundation for various precision interventional therapies.

He developed a magnetic multilayer soft robot for multi-target adhesion to achieve enhanced gastric ulcer therapy. The function and effectiveness of the robot have been successfully validated in the stomach of a living pig.

In addition, he proposed a dynamic obstacle avoidance control strategy based on hierarchical radar and artificial intelligence methods. This strategy provides optimized decision-making for the navigation of microrobot swarms in complex dynamic environments, while simultaneously ensuring obstacle avoidance stability and delivery efficiency.