Papers
5
Total Citations
21
H-Index
3
About
Orhan Ayit is a robotics researcher whose work spans human–robot collaboration, bipedal locomotion, and surgical robotics. His most impactful contribution, "Toward safe and high-performance human–robot collaboration via implementation of redundancy and understanding the effects of admittance term parameters" (2021, 9 citations), addresses a critical challenge in modern manufacturing: enabling humans to work safely alongside large-scale industrial robots. Ayit proposes a novel redundancy-based approach that balances performance and safety, offering a practical framework for collaborative environments. Earlier, in "A novel method for slip prediction of walking biped robots" (2015, 5 citations), he developed a measurement-driven algorithm that estimates Coulomb friction in real time, advancing the stability and reliability of bipedal locomotion. More recently, Ayit has focused on surgical robotics, contributing computationally efficient controller designs and simplified dynamic models for precise, minimally invasive procedures. His work on viscoelastic modeling of human nasal tissues (2018) further demonstrates his versatility, blending robotics with biomedical applications. With a growing citation record and contributions to both industrial and medical robotics, Ayit is establishing himself as a researcher dedicated to making robotic systems safer, more efficient, and more adaptable to human needs.
Research Focus
Key Achievements
Top Papers
- 1
- 2A novel method for slip prediction of walking biped robots5 citations · 2015
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