Farabi Kungozhin
Papers
2
Total Citations
15
H-Index
2
About
Farabi Kungozhin is a robotics researcher whose work centers on autonomous navigation and terrain-adaptive locomotion for hybrid mobile robots. His key contributions lie in developing supervisory control systems that enable robots to intelligently select and switch between different locomotion modes—such as walking or rolling—based on real-time environmental analysis. His most cited paper, “Locomotion Strategy Selection for a Hybrid Mobile Robot Using Time of Flight Depth Sensor” (2015, 13 citations), introduces a framework that uses depth sensing to classify terrain types and trigger appropriate gait or wheeled movement, significantly improving robot performance across varied surfaces. In related work, “Depth Image Based Terrain Recognition for Supervisory Control of a Hybrid Quadruped” (2014) further refines this approach, demonstrating real-time terrain classification for quadrupedal platforms. Though his citation counts are modest, Kungozhin’s research addresses a critical challenge in field robotics: enabling robots to operate autonomously in unstructured environments. His work is particularly relevant for search-and-rescue, exploration, and agricultural robotics, where adaptive locomotion is essential. By bridging computer vision and control systems, Kungozhin has contributed foundational methods for terrain-aware robotic mobility.
Research Focus
Key Achievements
Top Papers
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