Cristian Pop
Papers
7
Total Citations
35
H-Index
3
About
Cristian Pop is a robotics and computer vision researcher whose work bridges deep learning, mechatronic design, and industrial automation. His most cited paper, "Robotic Sorting of Used Button Cell Batteries: Utilizing Deep Learning" (12 citations), introduces an automated system that uses deep learning to classify button cell batteries by chemistry based on surface markings—a critical contribution to e-waste recycling and sustainable manufacturing. Pop’s research also spans visual servoing, where he developed a colored object detection algorithm for conveyor-based sorting (6 citations), and walking robot design, including the CAD and analytical modeling of a twelve-bar walking mechanism (6 citations) and a ten-bar articulated mechanism for quadruped locomotion (3 citations). His work on robot vision for bearings identification and sorting (3 citations) and dynamic analysis of quadruped robots using MBD ADAMS (3 citations) further showcases his expertise in integrating image processing, neural networks, and mechanical synthesis for real-world robotic applications. Pop’s contributions are particularly notable for their practical orientation—addressing challenges in recycling, manufacturing, and mobile robotics—and for combining theoretical modeling with prototype development, making his research directly applicable to industry and automation.
Research Focus
Key Achievements
Top Papers
- 1Robotic Sorting of Used Button Cell Batteries: Utilizing Deep Learning12 citations · 2018
- 2Colored object detection algorithm for visual-servoing application6 citations · 2012
- 3CAD DESIGN AND ANALYTICAL MODEL OF A TWELVE BAR WALKING MECHANISM6 citations · 2011
- 4
- 5Robot Vision Application for Bearings Identification and Sorting3 citations · 2012
- 6
- 7Image Processing and Artificial Neural Network for Robot Application2 citations · 2014