Sergey Khalapyan

Papers

12

Total Citations

60

H-Index

5

About

Sergey Khalapyan is a leading researcher in the design, control, and trajectory planning of parallel robotic systems, with a particular focus on avoiding singularity zones and optimizing workspace geometry. His work bridges fundamental robotics theory and practical biomedical applications. He has made major contributions to developing methods for determining design characteristics that ensure controllability of parallel robots, and pioneered a two-stage motion control method for planar 3-RPR mechanisms. Notably, Khalapyan developed a robotic system for blood serum aliquoting that integrates a neural network-based machine vision model to accurately detect boundary levels for pipette immersion—a critical innovation for laboratory diagnostics. His work on intelligent computing using neural networks for solving direct kinematics and closed-loop control of parallel robots has been widely cited (over 57 total citations). He has also advanced optimal trajectory planning using modified ant colony optimization algorithms and addressed multi-robot collision avoidance in biomaterial handling systems. His research on a sitting-type lower-limb rehabilitation system based on a spatial 3-PRRR parallel manipulator demonstrates the translational impact of his work in medical robotics.

Research Focus

Key Achievements

5
H-Index
12
Papers
60
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Issues of planning trajectory of parallel robots taking into account zones of singularity
12 citations · 2018
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 21

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago