Csaba Hajdu
Papers
9
Total Citations
69
H-Index
5
About
Csaba Hajdu is a robotics and autonomous systems researcher whose work centers on mobile robot navigation, path-tracking algorithms, and intelligent environment representation. He is perhaps best known for his contributions to the pure-pursuit trajectory-following algorithm, with his 2019 paper on novel pure-pursuit approaches accumulating 25 citations and a companion study on multi-goal enhancement drawing 11 more — together establishing him as a meaningful voice in trajectory tracking for both robotics and vehicular control. His research extends into robot environment representation, where he has pioneered the innovative fusion of fuzzy signature methods with quadtree data structures to enable efficient obstacle detection and spatial reasoning. Hajdu also explores motion planning using hybrid classical and reinforcement learning approaches, skid-steer robot control, and Industry 4.0 mobile robot design. More recently, he has ventured into drone-based agricultural protection through digital twin frameworks and semantic knowledge exchange between intelligent systems via tensor-based hypergraph formats. Across his body of work, Hajdu consistently bridges theoretical algorithmic development with practical implementation, making his research particularly valuable for engineers and students working at the intersection of autonomous vehicles, cognitive robotics, and smart cyber-physical systems.
Research Focus
Key Achievements
Top Papers
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- 3Digital Twin of Drone-based Protection of Agricultural Areas8 citations · 2022
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- 7Possible Control Methods for Skid-Steer Mobile Robot Platforms4 citations · 2020
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