KiBeom Kim

University of North Carolina at Chapel Hill

Papers

1

Total Citations

4

H-Index

1

About

KiBeom Kim is a roboticist whose research focuses on intelligent manipulation and motion planning for autonomous systems operating in complex, unstructured environments. His most-cited work, "Retrieving objects from clutter using a mobile robotic manipulator" (2019), addresses a fundamental challenge in service and industrial robotics: extracting a target object from a densely packed space without causing collisions. Kim’s key contribution is a novel task and motion planning framework that enables a mobile manipulator to strategically relocate obstacles, effectively reasoning about the physical interactions required to clear a path. This work has garnered 4 citations, laying a critical foundation for more advanced research in clutter handling and object retrieval. By tackling the high-density configuration problem, Kim’s research directly impacts applications ranging from warehouse logistics to assistive robotics, where robots must operate in human-centric, cluttered settings. His approach combines geometric reasoning with practical manipulation constraints, offering a scalable solution for robots to navigate and interact with disorderly environments. Kim’s work is essential reading for students and researchers interested in bridging the gap between high-level planning and low-level control in robotic manipulation.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Retrieving objects from clutter using a mobile robotic manipulator
4 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of North Carolina at Chapel Hill

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago