Changhwan Kim
Papers
4
Total Citations
71
H-Index
3
About
Changhwan Kim is a robotics researcher whose work spans robotic manipulation, motion planning, and multi-robot systems. His most significant contributions lie in the domain of object manipulation in cluttered environments, where he has developed innovative algorithms to address one of robotics' most persistent challenges: enabling robotic manipulators to efficiently grasp target objects when surrounded by densely packed obstacles in constrained spaces. Kim's most impactful work, "Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments" (2019), has garnered 60 citations, reflecting the robotics community's strong interest in practical solutions for real-world manipulation scenarios. This research introduced planning algorithms that intelligently relocate interfering objects to create collision-free manipulation paths — a critical capability for applications in warehouse automation and assistive robotics. He has continued advancing this area through Task and Motion Planning (TAMP) frameworks, combining local and global search strategies for more robust rearrangement solutions. Earlier in his career, Kim also explored multi-robot coordination, contributing a panoramic vision-based approach for formation keeping and cooperative localization. Across his body of work, Kim demonstrates a consistent focus on making robotic systems more capable of operating intelligently in complex, real-world environments.
Research Focus
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Top Papers
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