Hexiang Yuan
Papers
2
Total Citations
82
H-Index
2
About
Hexiang Yuan is a leading researcher in marine robotics and underwater artificial intelligence, with a focus on deep learning for autonomous perception and bio-inspired robotic design. His most cited work, “Real-time underwater object detection technology for complex underwater environments based on deep learning” (2024, 72 citations), addresses the critical challenge of poor optical image quality in marine settings, advancing real-time detection for environmental monitoring, resource development, and ecological protection. In parallel, his innovative paper “A Snake Eel Inspired Multi-joint Underwater Inspection Robot for Undersea Infrastructure Intelligent Maintenance” (2022, 10 citations) introduces a highly flexible, slim robotic platform modeled after snake eels, designed to navigate and inspect complex undersea structures with exceptional maneuverability. By replacing traditional bionic driving mechanisms with optimized joint arrangements, Yuan’s work enhances robotic passing ability and operational efficiency. His contributions bridge the gap between robust computer vision and agile robotic systems, offering practical solutions for intelligent maintenance of underwater infrastructure. With growing citation impact, Hexiang Yuan is establishing himself as a key innovator in the intersection of marine engineering and deep learning, driving forward the capabilities of autonomous underwater systems.
Research Focus
Key Achievements
Top Papers
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- 2