Hyung Gi Min
Papers
1
Total Citations
7
H-Index
1
About
Hyung Gi Min is a robotics researcher whose work centers on the integration of simulation environments, deep learning, and robotic control systems. His most impactful contribution, the paper “Implementation of a unified simulation for robot arm control with object detection based on ROS and Gazebo” (2020), presents a novel method for combining deep learning-based object detection with robotic arm control within a unified simulation framework. By leveraging the Robot Operating System (ROS) and the Gazebo simulator, Min demonstrated how open-source software libraries can be used to create realistic, scalable testbeds for intelligent automation. This approach has been cited 7 times, reflecting its practical value for researchers and engineers developing autonomous robotic systems. Min’s work is particularly notable for bridging the gap between simulation and real-world deployment, offering a reproducible pipeline that accelerates prototyping in robotics. His contributions are essential for students and researchers exploring the intersection of computer vision, control theory, and simulation-based robotics.
Research Focus
Key Achievements
Top Papers
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