Min-Jae Kim
Papers
1
Total Citations
4
H-Index
1
About
Dr. Min-Jae Kim is a robotics researcher whose work centers on computer vision and autonomous manipulation for industrial logistics. His most cited paper, "Box segmentation, position and size estimation for robotic box handling applications" (2022, 4 citations), tackles a core challenge in warehouse automation: enabling robots to reliably perceive and interact with boxes in cluttered environments. Dr. Kim developed a vision system that integrates color and depth data to segment boxes and estimate their precise position and dimensions, a critical capability for safe and efficient robotic grasping and handling. This contribution directly addresses the practical demands of modern logistics, where robots must adapt to varying box sizes and placements. While his citation count is modest, reflecting an early-career focus, the work demonstrates a strong applied impact, offering a robust solution that bridges computer vision and robotics. Dr. Kim’s research is particularly valuable for students and engineers interested in real-world robotic perception, as it emphasizes reliability and accuracy over theoretical complexity, laying a foundation for more advanced autonomous systems in warehousing and beyond.
Research Focus
Key Achievements
Top Papers
- 1