Tagir Abdullin

Lomonosov Moscow State University, Moscow State Technological University

Papers

Total Citations

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About

Tagir Abdullin’s research sits at the intersection of robotics, reconfigurable computing, and real-time control systems. His work focuses on leveraging field-programmable gate arrays (FPGAs) to accelerate computationally intensive tasks in collaborative robotics and industrial automation. A key contribution is the implementation of a hardware neuroaccelerator on an FPGA (Cyclone IV series) for collaborative robotics tasks, demonstrating how neural network inference can be offloaded to dedicated logic for faster, more efficient operation. He has also advanced the field of kinematic calculations, developing fast solvers for direct and inverse kinematic problems in multicomponent systems like industrial robots and multicoordinate machine tools. His 2021 paper on FPGA-based neuroaccelerators has garnered 5 citations, while his 2020 works on kinematic calculations and high-performance digital control systems have received 3 and 2 citations, respectively. Abdullin’s notable achievement includes designing a high-performance digital control system for machine tools and robots that ensures high productivity in solving inverse kinematic problems. His work is particularly relevant for students and researchers interested in embedded systems, hardware acceleration, and real-time robotics control.