Papers
2
Total Citations
24
H-Index
2
About
Mei Yu is a researcher advancing the frontiers of human-robot interaction and bio-inspired robotics. Her work centers on two key areas: identifying upper-limb movements for seamless human-machine collaboration, and developing intelligent path-planning algorithms for autonomous robotic systems. In her most cited study (2020, 19 citations), Yu pioneered the use of muscle shape change signals—an innovative alternative to conventional surface electromyogram (EMG) sensors—to decode limb movement intentions. This approach overcomes EMG’s vulnerability to electromagnetic interference, offering a more robust and practical interface for prosthetic control and assistive robotics. Earlier, Yu demonstrated foresight by applying genetic algorithms and modified dynamic programming to robotic fish path planning (2011, 5 citations), achieving optimal navigation in grid-based environments. This work laid groundwork for energy-efficient, autonomous underwater vehicles. Though her citation counts are modest, Yu’s contributions are notable for their interdisciplinary creativity—blending biomechanics, control theory, and evolutionary computation. Her research holds promise for more intuitive human-robot teams and smarter, adaptive robots in real-world settings.
Research Focus
Key Achievements
Top Papers
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