Papers

7

Total Citations

42

H-Index

4

About

Stanislav Shidlovskiy is a leading researcher in autonomous navigation and computer vision, with a focus on developing robust, vision-based systems for mobile robots and unmanned aerial vehicles. His work addresses critical challenges in scene matching, path tracking, and localization, particularly in environments where GPS or other external sensors are unreliable. Shidlovskiy’s most cited paper (2022, 16 citations) introduces a novel method for visual navigation that leverages street geometry to improve image alignment and servoing, enhancing positional accuracy without additional sensors. He has also pioneered the use of convolutional neural networks to detect false matches in aerial navigation systems (2021, 5 citations), significantly improving reliability over traditional statistical methods. Beyond navigation, Shidlovskiy contributes to energy-efficient autonomous systems, designing intelligent control algorithms for solar-powered robots (2018, 5 citations). His broader impact includes developing keypoint detection algorithms for obstacle and people recognition using histogram of oriented gradients and support vector machines (2018, 4 citations), as well as advancing SLAM-based local navigation for ground robots (2019, 3 citations). With a career spanning industrial automation and electron-beam welding (2016, 2 citations), Shidlovskiy’s work is essential for creating trustworthy, self-sufficient robotic systems.

Research Focus

Key Achievements

4
H-Index
7
Papers
42
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Visual Navigation and Path Tracking Using Street Geometry Information for Image Alignment and Servoing
16 citations · 2022
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: National Research Tomsk State University, Tomsk Polytechnic University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago