Spiriden Likothanassis
Papers
1
Total Citations
19
H-Index
1
About
Dr. Spiriden Likothanassis is a leading figure in agricultural robotics, specializing in autonomous navigation and perception for precision viticulture. His core research integrates computer vision, deep learning, and simultaneous localization and mapping (SLAM) to solve the unique challenges of unstructured field environments. His most influential work, "Loop Closure Detection and SLAM in Vineyards with Deep Semantic Cues" (2022, 19 citations), introduces a pioneering stereo vision-based Graph-SLAM pipeline that leverages deep semantic cues—such as vine trunks and trellis structures—to achieve robust loop closure detection. This innovation dramatically improves localization accuracy for mobile robots navigating the repetitive, visually ambiguous corridors of vineyards, directly addressing a critical bottleneck in automated cultivation. By fusing geometric constraints with semantic understanding, Likothanassis’s system enables reliable long-term autonomy for tasks like monitoring, spraying, and harvesting. His contributions are foundational to the emerging field of agricultural field robotics, bridging the gap between theoretical SLAM research and practical deployment in complex, real-world agricultural settings.
Research Focus
Key Achievements
Top Papers
- 1Loop Closure Detection and SLAM in Vineyards with Deep Semantic Cues19 citations · 2022