P. Mazurek
Papers
5
Total Citations
35
H-Index
4
About
P. Mazurek is a researcher specializing in robotics, computer vision, and autonomous navigation, with a particular focus on line-following mobile robots. Their major contributions center on developing robust algorithms for line trajectory estimation under challenging conditions, such as variable lighting, noise, and dim or degraded line markings. Mazurek pioneered the application of the Viterbi algorithm—traditionally used in communications—to robotic line tracking, introducing innovative variants like the History Dependent Viterbi Algorithm to improve navigation accuracy. Their work also integrates deep learning for dim line tracking, advancing the field’s ability to handle real-world imperfections. With over 35 combined citations across their most-cited papers, Mazurek’s research has demonstrated practical impact through Monte Carlo robustness verifications and experimental validations. Notable achievements include the systematic exploration of directional filters and track-before-detect approaches, which enhance the reliability of autonomous guided vehicles in industrial and service applications. Their publications provide foundational techniques for students and engineers seeking to design cost-effective, vision-based navigation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Directional Filter and the Viterbi Algorithm for Line Following Robots8 citations · 2014
- 3Viterbi Algorithm for Noise Line Following Robots6 citations · 2014
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- 5