Stanislav A. Eroshenko

Ural Federal University

Papers

3

Total Citations

7

H-Index

2

About

Stanislav A. Eroshenko is an emerging robotics and autonomous systems researcher whose work sits at the intersection of multi-spectral diagnostics, unmanned ground vehicles, and industrial inspection technologies. His research centers on the design and deployment of intelligent robotic platforms for automated equipment monitoring, with a particular focus on the Multi-Spectral Automatic Diagnostic (MAD) robot — a low-cost, open-source-based system engineered for real-world power infrastructure inspection. Eroshenko's contributions span both hardware prototyping and software integration, leveraging platforms such as ArduRover firmware to develop practical, field-ready diagnostic robots. A notable achievement in his portfolio is demonstrating that GNSS-based targeting can achieve sufficient precision for narrow-angle UV camera alignment in low-cost robotic systems — a meaningful step toward affordable autonomous inspection. His critical review of market-available multi-rotor drones for large-scale industrial facility inspection further reflects his commitment to bridging the gap between commercial technology and demanding real-world requirements. Though his publication record is still growing — with citations accumulating across his 2023 and 2024 works — Eroshenko represents a new generation of applied robotics researchers addressing urgent industrial automation challenges with pragmatic, accessible engineering solutions.

Research Focus

Key Achievements

2
H-Index
3
Papers
7
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
MAD Robot: Concept and Prototype Description of the Robot for Multi-Spectral Power Equipment Diagnostics. Part II
3 citations · 2023
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Ural Federal University

Top Papers

  1. 1
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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago