Joonhyung Sim
Papers
1
Total Citations
13
H-Index
1
About
Joonhyung Sim is a robotics researcher whose work focuses on the intersection of worker safety, collaborative robotics, and intelligent control systems. His primary research areas include mobile manipulation, human-robot interaction, and reinforcement learning for industrial automation. Sim’s most notable contribution is his 2021 paper, "Designing Path of Collision Avoidance for Mobile Manipulator in Worker Safety Monitoring System Using Reinforcement Learning," which has garnered 13 citations. In this work, he addresses a critical challenge in next-generation manufacturing: enabling mobile manipulators—robots that combine mobility with manipulation—to operate safely alongside human workers. By applying reinforcement learning to collision avoidance, Sim’s research provides a framework for simultaneous control of mobile manipulators, a task previously hindered by safety concerns. His work is particularly significant for advancing collaborative robot systems, where efficiency and worker protection must coexist. Sim’s contributions are helping to shape the future of industrial robotics, making automated processes safer and more adaptable in dynamic environments.
Research Focus
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Top Papers
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