Jeeseop Kim

Virginia Tech, California Institute of Technology

Papers

19

Total Citations

166

H-Index

8

About

Jeeseop Kim is a robotics researcher whose work sits at the intersection of legged locomotion, multi-agent systems, and safety-critical control. His most significant contributions center on cooperative locomotion for quadrupedal robots, where he has pioneered layered and hierarchical control frameworks that enable multiple holonomically constrained robots to collaboratively carry objects and navigate complex environments in real time. His 2023 paper on layered control for cooperative quadrupedal locomotion has already garnered 28 citations, reflecting the immediate impact of this foundational work. Kim has also advanced distributed data-driven predictive control methods grounded in behavioral systems theory, offering scalable solutions for sophisticated multi-agent legged systems. A recurring theme in his research is safety-critical control, particularly the application of Control Barrier Functions to resolve conflicting safety constraints — work that has attracted growing attention across the robotics community. Beyond quadrupeds, Kim has explored bio-inspired tail mechanisms for disturbance rejection, bipedal locomotion on underactuated humanoids, and even medical robotics applications such as robotic cardiopulmonary resuscitation. His diverse yet cohesive body of work, spanning over 130 cumulative citations, marks him as an emerging and versatile voice in modern robotics and autonomous systems research.

Research Focus

Key Achievements

8
H-Index
19
Papers
166
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Layered Control for Cooperative Locomotion of Two Quadrupedal Robots: Centralized and Distributed Approaches
28 citations · 2023
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 29
🏛 Institutions: Virginia Tech, California Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago