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About

Gabriel Fedorko is a researcher focused on advancing industrial automation and robotics, with key contributions in autonomous guided vehicle (AGV) systems, inertial navigation for robotics, and human-robot collaboration. His most cited work, "Comparison of the Traditional and Autonomous AGV Systems" (2017, 29 citations), explores how AGVs revolutionize internal logistics by enhancing efficiency, precision, and cost-effectiveness. He further investigates production system productivity through inertial navigation integration, analyzing gyroscopes and accelerometers to improve robot control dynamics (2015, 17 citations). Fedorko also addresses the critical intersection of safety and efficiency in semi-automatic production lines, developing visual work instructions to ensure smooth human-robot interaction (2016, 6 citations). His research extends to measuring local muscular load via dataloggers and examining how production technologies—additive versus conventional—affect robotic arm positioning accuracy for low-handling weights (2021, 2 citations). With a cumulative impact of over 56 citations, Fedorko’s work bridges theoretical advancements and practical applications, offering valuable insights for students and researchers in manufacturing, logistics, and robotics. His dedication to optimizing automated systems and human-machine collaboration underscores his role in shaping modern industrial practices.