Lesia Mochurad
Papers
5
Total Citations
57
H-Index
3
About
Lesia Mochurad is a robotics researcher whose work focuses on autonomous navigation and human-robot interaction. Her primary research areas include obstacle detection for mobile robots, LiDAR-based localization, and machine learning for robotic manipulation. One of her most impactful contributions is an obstacle-finding approach for autonomous mobile robots using 2D LiDAR data (2023, 27 citations), which addresses a critical challenge in indoor navigation by improving the accuracy of obstacle detection and positioning. She has also advanced the field through parallelization techniques for LiDAR coordinate determination using genetic algorithms and OpenMP (2021, 13 citations), enhancing computational efficiency. Mochurad’s work extends to practical robotic tasks, such as developing machine learning methods for opening doors (2023, 12 citations) and recognizing door handles with RGBD cameras (2024, 2 citations). Her recent research on autopilot-based trajectory control for unmanned aerial vehicles (2024) further demonstrates her versatility. With a growing citation record and a focus on real-world applications, Mochurad’s contributions are paving the way for more autonomous, adaptable robotic systems capable of navigating and interacting with complex environments.
Research Focus
Key Achievements
Top Papers
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