Papers

5

Total Citations

42

H-Index

4

About

Divya Shah is a roboticist whose research focuses on the design and optimization of dexterous, tendon-driven mechanisms for humanoid robots and human-robot collaboration. Her major contributions lie in the comparative analysis and development of compact, lightweight wrist mechanisms, as demonstrated in her most-cited work, "A Comparison of Robot Wrist Implementations for the iCub Humanoid" (21 citations), which systematically evaluates five orientational mechanisms to improve the iCub platform’s dexterity. She also advanced tendon-routing theory in "Constant Length Tendon Routing Mechanism through Axial Joint" (9 citations), addressing kinematic couplings critical for safe, backdrivable robots. Her work on parallel kinematic mechanisms, such as the N-UU class (6 citations), provides foundational workspace analyses for singularity-free robot wrists. Notably, Shah contributes to the ergoCub project, designing new joint modules for ergonomic human-robot collaboration in industrial and healthcare settings (4 citations). Her expertise extends to optimizing redundant robotic systems for automated fiber placement (2 citations), showcasing versatility in both humanoid and manufacturing applications. With a clear trajectory from theoretical mechanism analysis to applied humanoid design, Shah’s research directly impacts the development of safer, more capable collaborative robots.

Research Focus

Key Achievements

4
H-Index
5
Papers
42
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
A Comparison of Robot Wrist Implementations for the iCub Humanoid †
21 citations · 2019
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Italian Institute of Technology, Laboratoire des Sciences du Numérique de Nantes

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago