Daniel Huczala
Papers
8
Total Citations
91
H-Index
7
About
Daniel Huczala is a robotics and automation researcher whose work spans industrial robot design, sensor systems, and intelligent manufacturing environments. His research centers on three interconnected themes: the synthesis and optimization of robotic manipulator kinematics, advanced sensing and calibration methods for robotic workcells, and autonomous guided vehicle localization within smart infrastructure. Among his most significant contributions is his investigation into laser line triangulation sensors, demonstrating how incidence angle affects reflected laser intensity across industrial materials — work that has garnered 18 citations and carries direct practical value for quality control applications. His parallel efforts in kinematic structure synthesis, including genetic optimization of manipulator link geometries and energy-consumption-driven dimensional optimization, reflect a commitment to task-specific, cost-effective robot design that challenges the dominance of universal six-axis configurations. Huczala has also advanced the field of robotic workcell intelligence, proposing camera-based calibration methods using Jacobian matrix approaches and developing a Shared Sensory System that repurposes smart building infrastructure for AGV localization. His 2022 RobKin Interpreter further demonstrates his drive toward standardization and interoperability in robotics. Collectively accumulating over 90 citations, his body of work positions him as a versatile and practically-minded contributor to modern industrial robotics research.
Research Focus
Key Achievements
Top Papers
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- 4Camera-Based Method for Identification of the Layout of a Robotic Workcell12 citations · 2020
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- 6DIMENSIONAL OPTIMIZATION OF THE ROBOTIC ARM TO REDUCE ENERGY CONSUMPTION9 citations · 2020
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- 8An Automated Conversion Between Selected Robot Kinematic Representations6 citations · 2022