Papers
4
Total Citations
12
H-Index
3
About
Anatoliy Andrakhanov is a pioneering researcher in mobile robotics, specializing in traversability estimation and navigation systems for outdoor robots operating in heterogeneous, a priori unknown environments. His core contributions center on applying inductive modeling, particularly the Group Method of Data Handling (GMDH), to solve critical challenges in autonomous motion control. Andrakhanov developed a practical traversability estimation system that enables mobile robots to assess underlying surface characteristics in real time, a foundational capability for safe off-road navigation. He also introduced the first learning-based navigation system using GMDH algorithms, allowing robots to adapt their movement strategies without pre-programmed maps. His work on obstacle recognition, dating back to 2009, established a close link between perception and control, influencing subsequent inductive approaches in robotics. While his most-cited papers (2017) each hold 3–4 citations, their impact lies in demonstrating how self-organizing, data-driven methods can replace traditional rule-based systems in complex terrains. Andrakhanov’s research bridges machine learning and field robotics, offering practical solutions for autonomous exploration, search-and-rescue, and agricultural robots. His inductive modeling framework remains a valuable alternative for researchers seeking lightweight, adaptive navigation in unstructured environments.
Research Focus
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Top Papers
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