Hasan Komur

Selçuk University, Konya Technical University

Papers

Total Citations

H-Index

About

Hasan Komur is a researcher focused on human-robot interaction (HRI) and robotic imitation learning, with a particular emphasis on developing intuitive interfaces between humans and robotic systems. His work centers on enabling robots to learn from and respond to human gestures, bridging the gap between human movement and robotic control. In his most-cited study, "Robot imitation of human arm via Artificial Neural Network" (2014, 12 citations), Komur designed a robotic arm that could replicate human arm movements by using potentiometers to capture joint data from a human arm. This data was then classified using an Artificial Neural Network, demonstrating a foundational approach to teaching robots through demonstration—a key contribution to the field of imitation learning. His later work, "Human Robot Interaction to Guide a Person" (2018, 2 citations), explored a different facet of HRI: using a robotic arm to physically guide a human. In an experiment with 15 participants, Komur showed that effective interaction could be established between a person and a robot for guidance tasks. While his citation counts are modest, these studies represent early, practical steps in creating more responsive and assistive robotic systems, contributing to the growing body of work on safe and intuitive human-robot collaboration.