Andrey Alepko

About

Andrey Alepko is at the forefront of advancing human-robot collaboration and intelligent manufacturing systems. His research focuses on developing intuitive, contactless human-machine interfaces that eliminate the need for extensive operator training, making industrial robotics more accessible and efficient. Alepko’s most cited work, “Control System of Collaborative Robotic Based on the Methods of Contactless Recognition of Human Actions” (2019, 15 citations), pioneers methods for natural gesture-based interaction between humans and robots. He has also made significant contributions to automated manufacturing quality control, creating algorithms for the automated determination of heating areas during metal processing using dual-camera visible and thermal imaging systems (2021, 13 citations). Demonstrating a strong commitment to hardware acceleration for real-time robotics, Alepko has implemented neuro-accelerators on FPGAs for collaborative robotics tasks and developed a heterogeneous neuromorphic processor based on the open-source RISC-V architecture, integrating a reconfigurable neural network accelerator for real-time applications. His work bridges the gap between advanced sensing, embedded computing, and practical industrial automation, positioning him as a key innovator in next-generation collaborative robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Control System of Collaborative Robotic Based on the Methods of Contactless Recognition of Human Actions

   15 citations · 2019
2. 2
   Algorithm for the automated determination of heating areas during metal processing with numerically controlled machines

   13 citations · 2021
3. 3
   Using neuro-accelerators on FPGAs in collaborative robotics tasks

   5 citations · 2021
4. 4
   Heterogeneous neuromorphic processor based on RISC-V architecture for real-time robotics tasks

   3 citations · 2020

Key Collaborators

Contact & Links