Dong Gyu Park

Seoul National University of Science and Technology

Papers

Total Citations

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About

Dong Gyu Park is a robotics researcher whose work centers on autonomous navigation, 3D perception, and mobile manipulation, with a particular focus on indoor self-driving systems. His most cited paper, "DBSCAN and Yolov5 based 3D object detection and its adaptation to a mobile platform" (2024, 3 citations), introduces a novel fusion of density-based clustering and deep learning for real-time 3D object detection, enabling mobile robots to perceive and interact with their environment more reliably. In his earlier work, "ROS-based Control System for Localization and Object Identification of Indoor Self-driving Mobile Robot" (2021, 2 citations), Park developed a complete control architecture for logistics automation, integrating ROS, OpenCR microcontrollers, and sensor fusion (IMU and encoder odometry) with an Adaptive Monte Carlo Localization algorithm to achieve robust robot positioning and real-time obstacle avoidance. This system was designed to autonomously sort and transport boxes to target destinations, addressing key challenges in warehouse unmanned operations. Park’s contributions bridge practical robotics and perception, demonstrating how classical algorithms and modern deep learning can be combined for real-world deployment. His work is especially relevant for researchers and students interested in autonomous mobile robots, sensor fusion, and logistics automation.