Petar Durdevic
Papers
7
Total Citations
111
H-Index
5
About
Petar Durdevic is a researcher whose work spans robotics, computer vision, and industrial inspection systems, with a particular focus on applying deep learning to autonomous systems and 3D data processing. His most influential contribution is a comprehensive survey on point cloud-based 3D defect classification and segmentation for industrial systems (2024), which has already garnered 38 citations and serves as a key reference for researchers working at the intersection of condition monitoring and deep learning. Complementing this, his survey on visual servoing systems (2021, 29 citations) has become a widely referenced resource bridging classical and deep learning-based approaches to robot guidance. Durdevic's work extends prominently into pipeline inspection robotics, most notably through the Smart-Spider project (2018, 26 citations), which introduced an autonomous inline inspection robot designed for challenging offshore oil and gas environments. His research also addresses autonomous ground robot navigation using monocular camera systems and multiple deep learning models, reflecting a broader commitment to enabling robust, sensor-driven autonomy. Even his earlier work on hybrid sliding mode control for balancing robots demonstrates a longstanding engagement with challenging control problems. Collectively, Durdevic's output positions him as a versatile contributor to intelligent industrial robotics and autonomous perception systems.
Research Focus
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