Byeong-Min Jeong
Papers
2
Total Citations
13
H-Index
2
About
Byeong-Min Jeong is a rising researcher at the forefront of robotic autonomy and intelligent perception. His work primarily focuses on integrating foundation models into robotic systems and advancing 3-D dynamic environment mapping. In his highly cited 2024 survey, "Unlocking Robotic Autonomy: A Survey on the Applications of Foundation Models," Jeong provides a comprehensive roadmap for leveraging large-scale pre-trained models to enhance robotic decision-making and adaptability—a paper that has already garnered 11 citations shortly after publication. He also made notable contributions to spatial understanding with "DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory," which addresses the critical challenge of representing dynamic 3-D environments for navigation and manipulation tasks. This work bridges a gap in traditional occupancy mapping, which has largely been limited to static 2-D settings. Jeong’s research is shaping how robots perceive and interact with complex, changing surroundings, laying the groundwork for more autonomous and intelligent systems. His growing citation record reflects the timely importance of his contributions to the robotics community.
Research Focus
Key Achievements
Top Papers
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- 2