Kangjin Kim

Arizona State University

Papers

8

Total Citations

126

H-Index

6

About

Kangjin Kim is a roboticist whose research lies at the intersection of formal methods, control synthesis, and multi-agent systems, with a central focus on guaranteeing safe and provably correct robot behavior. His most influential work tackles the critical challenge of automatically revising high-level task specifications—expressed as temporal logic or automata—when they are found to be unrealizable. In a trio of highly cited papers (2012–2015, accumulating over 80 citations), Kim formalized the "minimal revision problem" for specification automata, developing both exact and approximate solutions that allow a robot to automatically adjust its mission requirements while preserving as much of the original intent as possible. This work provides a foundational tool for bridging the gap between high-level task planning and low-level control. Beyond specification revision, Kim contributed to making formal methods more accessible, notably through the "LTLvis" graphical language and interface for LTL motion planning. He also advanced distributed multi-robot coordination with the DisCoF framework, enabling cooperative pathfinding for robots with limited sensing and communication. Through these contributions, Kim has helped move provably correct robotics from theory toward practical, real-world deployment.

Research Focus

Key Achievements

6
H-Index
8
Papers
126
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
On the minimal revision problem of specification automata
30 citations · 2015
📈 Most Prolific Year: 2015 (3 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Arizona State University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago