Papers

5

Total Citations

19

H-Index

3

About

Victor Cobilean is a robotics researcher whose work focuses on the intersection of robotic manipulation, computer vision, and workspace optimization. His primary research areas include parallel robot kinematics, 3D vision processing for industrial automation, and trajectory planning. Cobilean’s most notable contribution is a novel method for industrial workspace detection that combines 2D and 3D vision processing to enable robotic arms to operate intelligently in dynamic environments—a significant step toward practical autonomous manufacturing. This work has already garnered 8 citations since its 2024 publication. He has also made important contributions to the analysis and optimization of parallel robots, including a kinematic performance analysis of a 3-R(RPRGR)RR planar parallel robot and a comparative study of CAD optimization features for the workspace of 3-DOF Delta robots. His research on shape optimization for prismatic actuated parallel robots and trajectory planning for planar parallel robots demonstrates a systematic approach to improving robotic precision and efficiency. Cobilean’s work is particularly relevant for researchers and engineers developing adaptive robotic systems for modern industrial applications.

Research Focus

Key Achievements

3
H-Index
5
Papers
19
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Industrial workspace detection of a robotic arm using combined 2D and 3D vision processing
8 citations · 2024
📈 Most Prolific Year: 2021 (4 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Virginia Commonwealth University, Technical University of Cluj-Napoca

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago