Miloš Petrović
Papers
4
Total Citations
36
H-Index
4
About
Miloš Petrović is a leading researcher at the intersection of manufacturing automation, deep learning, and human-robot collaboration. His work primarily focuses on creating intelligent, flexible systems for modern industry, addressing the critical challenges of small-batch production and workplace safety. Petrović’s major contributions include pioneering the use of the Segment Anything Model (SAM) for versatile waste sorting in flexible manufacturing, a study that has already garnered 14 citations and is shaping the future of automated recycling in LEAN environments. He has also advanced workplace safety by developing deep learning frameworks to recognize unsafe operator acts, a highly cited work (11 citations) that bridges computer vision and industrial ergonomics. In human-robot interaction, Petrović has innovated by using EMG sensors and 3D pose estimation to assess collaborative polishing tasks, and he has developed sophisticated Cartesian stiffness shaping methods for compliant robots using incremental learning and sequential quadratic programming. His research, consistently published in top venues, is driving the next generation of adaptive, safe, and efficient manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Deep Learning-Based Recognition of Unsafe Acts in Manufacturing Industry11 citations · 2023
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