Papers
7
Total Citations
68
H-Index
4
About
A. A. Zelenskii is a researcher specializing in robotics, autonomous navigation, computer vision, and industrial automation. His work sits at the intersection of machine learning and practical robotic systems, with a focus on making intelligent machines more capable and efficient in real-world manufacturing environments. Zelenskii's most impactful contribution is his development of a 3-D Binary Micro-block Difference method for action recognition in robotics and manufacturing automation, which has garnered 35 citations since its 2021 publication, establishing him as a notable voice in gesture and motion recognition research. Complementing this, his investigations into SLAM-based robot navigation and multimodal image inpainting address the persistent challenge of depth map reconstruction — particularly the problem of missing or obscured regions caused by poor lighting conditions — each accumulating 10 citations. Beyond perception, Zelenskii has made meaningful contributions to robot control and hardware efficiency, exploring deep learning-driven collaborative robot systems, fast kinematic solvers for industrial manipulators, and FPGA-based digital control architectures that enhance processing speed for inverse kinematics. Together, his body of work reflects a comprehensive engineering vision: building smarter, faster, and more reliable robotic systems from sensor input through to physical motion control.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Multimodal image inpainting for an autonomous robot navigation application10 citations · 2021
- 4
- 5
- 6Fast Kinematic Calculations for Industrial Robots3 citations · 2020
- 7