Yurii Ilyukhin
Papers
6
Total Citations
35
H-Index
3
About
Yurii Ilyukhin is a researcher advancing the frontiers of human-robot collaboration (HRC) and autonomous robotic systems. His work centers on three key areas: human activity recognition for safe, efficient HRC in smart manufacturing; multimodal image processing for robot navigation; and hardware-accelerated neural networks on FPGAs for real-time robotic tasks. His most cited paper (2020, 12 citations) introduces a crucial framework for recognizing human actions to enable seamless collaboration between operators and robots in dynamic industrial environments. A second highly cited work (2021, 10 citations) presents an automated pipeline for multimodal image inpainting, recovering missing depth map holes to improve 3-D scene understanding for autonomous navigation. Ilyukhin also demonstrates practical innovation by implementing a neuro-accelerator on a Cyclone IV FPGA (2021, 5 citations), showing how hardware constraints can be overcome for collaborative robotics. His additional contributions include memory-centric control system models for industrial robots and depth map reconstruction methods for mechatronic systems. With a growing citation record and a focus on bridging perception, hardware acceleration, and human-robot interaction, Ilyukhin is shaping the next generation of intelligent, collaborative manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1Human activity recognition for efficient human-robot collaboration12 citations · 2020
- 2Multimodal image inpainting for an autonomous robot navigation application10 citations · 2021
- 3Using neuro-accelerators on FPGAs in collaborative robotics tasks5 citations · 2021
- 4Memory-centric models of industrial robots control systems3 citations · 2021
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