Olena Pavliuk
Papers
1
Total Citations
9
H-Index
1
About
Olena Pavliuk is a researcher specializing in the intersection of machine learning, industrial automation, and energy management, with a particular focus on autonomous guided vehicles (AGVs). Her most-cited work, "The forecast of the AGV battery discharging via the machine learning methods" (2022, 9 citations), addresses a critical challenge in logistics and manufacturing: predicting battery depletion in AGVs to prevent operational downtime. In this study, she critically reviewed existing approaches to residual charge processing and proposed a novel experimental setup for collecting historical data from an AGV Formica 1, developed by AIUT company. By applying machine learning methods to the collected time-series data, Pavliuk demonstrated how predictive models can enhance battery management and operational efficiency. Her contribution lies in bridging theoretical ML techniques with practical industrial applications, offering a data-driven solution to a real-world problem. Though early in her career, her work has already garnered attention for its applied relevance, and she continues to advance research in intelligent energy systems and predictive maintenance for autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1