Sung‐Gyu Im
Papers
1
Total Citations
11
H-Index
1
About
Sung-Gyu Im is a researcher specializing in multi-robot systems, visual simultaneous localization and mapping (SLAM), and omnidirectional vision. His work addresses critical challenges in autonomous navigation and cooperative control, particularly through the integration of fisheye lens cameras for enhanced environmental perception. His most-cited paper, "Multi-Robot Avoidance Control Based on Omni-Directional Visual SLAM with a Fisheye Lens Camera" (2018), with 11 citations, introduces a novel framework that enables multiple robots to navigate and avoid collisions in dynamic environments using a single, wide-angle visual sensor. This contribution is notable for its practical approach to reducing computational complexity while improving robustness in real-world scenarios. Im’s research bridges the gap between theoretical SLAM algorithms and applied multi-robot coordination, offering scalable solutions for industrial automation, search-and-rescue operations, and autonomous exploration. His work has been recognized for its potential to advance decentralized robotic systems, and he continues to explore sensor fusion and real-time control strategies. For students and researchers, Im’s studies provide foundational insights into the intersection of computer vision, robotics, and multi-agent systems, highlighting the importance of efficient, low-cost sensing in complex environments.
Research Focus
Key Achievements
Top Papers
- 1