Papers

2

Total Citations

49

H-Index

2

About

Natalia Kryvinska is a leading researcher in the fields of robotics, navigation systems, and sensor data processing. Her work focuses on enhancing the precision and reliability of positioning technologies, particularly for mobile robots and autonomous vehicles. A major contribution is her pioneering analysis of MEMS gyroscope random errors using the Allan Variance method, which directly addresses the critical challenge of estimating movement and orientation in strapdown inertial navigation systems. This highly influential work, published in 2020, has already garnered 36 citations, underscoring its impact on improving sensor accuracy for robotic positioning. Additionally, Kryvinska has advanced computational efficiency in lidar coordinate determination by developing a parallelized genetic algorithm leveraging OpenMP technology. This 2021 study, with 13 citations, demonstrates her commitment to solving real-world problems in route planning, flight control, and machine learning. Through her innovative integration of error analysis and parallel computing, Kryvinska continues to shape the future of autonomous navigation and robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
49
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Strapdown Inertial Navigation Systems for Positioning Mobile Robots—MEMS Gyroscopes Random Errors Analysis Using Allan Variance Method
36 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Applied Sciences Technikum Wien, Comenius University Bratislava

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago