Alexander Lomakin
Papers
3
Total Citations
30
H-Index
3
About
Alexander Lomakin is a robotics researcher whose work focuses on advancing the reliability, control, and autonomy of robotic systems. His key research areas include fault detection and identification, dynamic parameter estimation, and model predictive control for manipulation. Lomakin’s major contributions are threefold: he developed a reliable algebraic method for detecting and identifying faults in rigid robots, accounting for additive faults and external forces—a critical step toward safer, more resilient automation. He also pioneered an approach for identifying dynamic base parameters using polynomial approximation, enabling accurate modeling from measurable signals alone. Additionally, he proposed a generic manipulation framework based on model predictive interaction control, hierarchically decomposing complex tasks into primitives for improved execution. Though his most-cited works currently range from 8 to 13 citations, these papers—published between 2020 and 2022—represent foundational steps in practical robot diagnostics and control. Lomakin’s work is particularly notable for its emphasis on algebraic and optimization-based methods that bridge theory and real-world application, making him a promising voice in the field of robotic manipulation and system reliability.
Research Focus
Key Achievements
Top Papers
- 1Reliable Algebraic Fault Detection and Identification of Robots13 citations · 2022
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