Tarik Yigit
Papers
3
Total Citations
10
H-Index
2
About
Tarik Yigit is a robotics researcher whose work bridges autonomous navigation, human-robot interaction, and precision agriculture. His primary research areas include human-following autonomous systems, multi-sensor 3D scanning, and mission planning for unmanned vehicles. Yigit made a notable contribution during the COVID-19 pandemic by developing optimal trajectory algorithms for human-following shopping carts, a gesture-based contactless system designed to reduce physical contact in public spaces. This work, which has garnered 5 citations, demonstrates his focus on socially relevant robotics applications. In the domain of sensing, he pioneered an auto-calibrated 3D hyperspectral scanning framework that integrates heterogeneous cameras and lights with spectrally-optimal next-best-view planning, addressing a longstanding challenge in combining hyperspectral imaging with 3D scanning for automation. His research also extends to agricultural robotics, where he developed resolution-optimal, energy-constrained mission planning algorithms for unmanned aerial and ground vehicles conducting crop inspections. With a total of 10 citations across his most-cited works, Yigit’s contributions are particularly valuable for their practical applications in public health, precision agriculture, and autonomous sensing—fields where his innovations offer scalable, real-world solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3