Meiying Zhang
Papers
6
Total Citations
55
H-Index
4
About
Meiying Zhang is a robotics researcher whose work centers on two key areas: underwater image processing and safe human-robot interaction. Her most impactful contribution, an improved K-means algorithm for underwater image background segmentation (2021, 26 citations), addresses the critical challenge of improper K value determination in underwater environments, significantly enhancing segmentation accuracy where conventional methods fail. In parallel, Zhang has made substantial contributions to robotic safety through the design of passive force and torque limiting devices. Her 2015 paper on force capabilities of serial robots with passive isotropic force limiters (9 citations) and subsequent work on optimal design of safe planar manipulators (8 citations) established foundational principles for bounding forces during human-robot cooperation. Her 2017 static analysis of elastic force and torque limiters (6 citations) further advanced this field by demonstrating how single elastic components can effectively limit applied forces. Zhang’s research bridges computer vision and mechanical design, offering practical solutions for safer, more reliable robotic systems in both underwater exploration and collaborative manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1An improved K-means algorithm for underwater image background segmentation26 citations · 2021
- 2
- 3Optimal Design of Safe Planar Manipulators Using Passive Torque Limiters8 citations · 2015
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