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About

Jinchang Fan is a leading researcher in underwater robotics, specializing in autonomous systems for industrial maintenance and marine infrastructure. His primary contributions center on developing intelligent, self-adaptive robots for cleaning steel pipes on offshore oil platforms—a challenging task due to variable pipe diameters and harsh underwater environments. Fan’s most influential work, an underwater climbing robot with a passive roll joint and combined magnet adhesion units (54 citations), introduced a novel self-adaption mechanism that dramatically improves mobility and stability. He further advanced the field with an online optimized control system using a fusion bat algorithm (12 citations), enabling more effective localization and autonomous operation in complex marine settings. Fan has also pioneered real-time panoramic navigation systems for underwater cleaning robots, allowing operators to monitor surroundings and cleaning progress in unknown environments. His broader portfolio includes brain-computer interface-controlled hand exoskeletons for cerebrum plasticity training and teleoperation systems enhanced by head-up display (HUD) techniques. Through these innovations, Fan has established himself as a key figure in practical underwater robotics, bridging the gap between theoretical control methods and real-world industrial applications.