Papers
11
Total Citations
120
H-Index
7
About
Oleksiy Kozlov is a prominent researcher specializing in intelligent control systems, mobile robotics, and computational intelligence, with particular expertise in the design and optimization of autonomous systems operating in challenging environments. His most significant contributions center on developing neuro-fuzzy observers and mathematical models for determining clamping forces in magnetically-operated mobile robots capable of traversing inclined and vertical ferromagnetic surfaces — a technically demanding problem with important industrial inspection applications. His 2016 foundational paper on neuro-fuzzy clamping force observers has garnered 28 citations, establishing a framework that subsequent works have built upon and refined. Kozlov's research portfolio demonstrates a sophisticated integration of field theory, ANFIS-based hybrid computing, and bioinspired optimization techniques. His work has progressively evolved from fundamental magnetic modeling to IoT-enabled remote control architectures and swarm intelligence-based fuzzy system optimization, reflecting both depth and adaptability in his research trajectory. Notable contributions include neural controllers for caterpillar robots, neuroevolutionary design approaches for complex multicoordinate plants, and structural-parametric optimization of fuzzy systems for quadrotor drones. With over 120 cumulative citations across his top publications, Kozlov's work meaningfully advances the field of intelligent autonomous robotics, offering practical solutions for remote inspection and industrial automation applications.
Research Focus
Key Achievements
Top Papers
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- 8Neural Controller for Mobile Multipurpose Caterpillar Robot7 citations · 2019
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- 10Remote IoT-based Control System of the Mobile Caterpillar Robot.5 citations · 2020