Hongjie Fan

Papers

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About

Hongjie Fan’s research lies at the intersection of bio-inspired robotics, intelligent control, and surgical automation, with a focus on enhancing perception and actuation in complex environments. A key contribution is their work on the artificial lateral line system (ALLS), where they pioneered optimal sensor placement strategies for flow parametric identification—a critical step toward achieving closed-loop control of underwater robotic fish. This work, cited 8 times, addresses the fundamental challenge of sensor configuration that directly impacts the accuracy of flow-field estimation. More recently, Fan has advanced surgical robotics through the development of a magnetic actuated flexible-joint robotic surgical camera system. By integrating a virtual muscle-model-modified reinforcement learning framework, they achieved precise tilt motion control for laparoscopic cameras, overcoming variability in magnetic actuation to improve surgical dexterity and extend operational periods. This innovative approach, already garnering 3 citations, demonstrates Fan’s ability to merge machine learning with mechanical design. Their work is notable for bridging theoretical control methods with practical robotic applications, offering scalable solutions for both underwater exploration and minimally invasive surgery.