Alexei Zakharov

Papers

Total Citations

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About

Alexei Zakharov’s research centers on robotics and computational intelligence, with a specific focus on parameter identification for robotic systems using evolutionary algorithms. His major contribution lies in demonstrating that genetic algorithms (GAs) can effectively and accurately identify the inverse dynamics parameters of a robot arm, even when the hardware is constrained by low-resolution position encoders. This work is significant because it reduces reliance on high-cost sensors, making advanced robotic control more accessible. His most cited paper, “Parameter Identification of a Robot Arm Using Genetic Algorithms” (2001), has garnered 13 citations, while a follow-up study in 2003, “Genetic Algorithms Based Identification Method for a Robot Arm,” has 6 citations. Together, these papers establish a foundational method that requires only position feedback, highlighting the robustness of GAs in handling noisy or limited data. Zakharov’s achievements showcase a practical, cost-effective approach to robot calibration, offering valuable insights for researchers and students in robotics, control systems, and evolutionary computation.