Kaya Turgut
Papers
12
Total Citations
60
H-Index
5
About
Kaya Turgut is a robotics and computer vision researcher whose work spans two deeply interconnected domains: autonomous 3D object reconstruction using industrial robotic systems and semantic place classification for mobile robots. His foundational 2014 paper on 3D visualization using laser profile sensors and industrial robot arms established a framework for applications in automated inspection and geometric reverse engineering, earning 11 citations and setting the stage for a sustained research trajectory. Building on this, Turgut developed increasingly sophisticated reconstruction methods, including the surface profile-guided scanning approach and the SPGS algorithm, collectively advancing the field of autonomous object digitization. Equally notable is his contributions to mobile robot perception: his 2021 deep learning architecture, 2DLaserNet, tackled the challenging problem of doorway classification from 2D laser scans — a gap overlooked by prior work — garnering 10 citations. His broader interests in point cloud segmentation, local coordinate frame determination, and search-and-rescue robotics using PointNet further demonstrate his versatility. With a body of work accumulating over 50 citations, Turgut represents an emerging voice bridging industrial robotics, deep learning, and autonomous spatial understanding.
Research Focus
Key Achievements
Top Papers
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- 4A robotic system for autonomous 3-D surface reconstruction of objects5 citations · 2017
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