Papers
2
Total Citations
19
H-Index
2
About
Can Shen is a rising researcher in bio-inspired robotics and fluid dynamics, with a focus on the hydrodynamic performance of self-propelled robot fish. Their key research areas include artificial lateral line (ALL) sensing, obstacle perception in aquatic environments, and robot fish navigation in constrained spaces like pipelines. Shen’s major contributions involve characterizing flow fields around robot fish as they approach static obstacles, revealing how pressure distribution on the fish body surface changes with separation distance—critical for improving autonomous obstacle avoidance in still water. This work, published in 2023, has garnered 12 citations, demonstrating its early impact. In 2024, Shen extended this research to pipeline environments, studying the unique hydrodynamic challenges of swimming in confined spaces, a study that has already earned 7 citations. These contributions are notable for advancing the practical deployment of robot fish in underwater inspection and environmental monitoring, where robust sensing and maneuverability are essential. Shen’s work bridges fundamental fluid mechanics and applied robotics, offering insights that could inspire next-generation autonomous underwater vehicles.
Research Focus
Key Achievements
Top Papers
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