Joong Bae Kim

Electronics and Telecommunications Research Institute

Papers

Total Citations

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About

Joong Bae Kim is a researcher whose work lies at the intersection of robotics, automation, and computer vision, with a particular focus on solving the challenges posed by deformable objects. His most influential contribution, the 2013 survey "A Survey on Robot Teaching: Categorization and Brief Review" (30 citations), addresses a critical gap in the field by providing a structured categorization of robot teaching systems. This framework has helped organize a previously fragmented research area, offering a valuable reference for scholars and engineers working on intuitive human-robot interaction and skill transfer. More recently, Kim has tackled the practical, high-stakes problem of automating wire harness assembly—a task still largely performed by humans due to its difficulty. In his 2022 paper, "Vision Based Deformable Wires Recognition using Point Cloud in Wire Harness Supply" (3 citations), he proposes a novel vision-based method for recognizing thin, deformable wires using point cloud data. This work demonstrates his commitment to advancing industrial automation by overcoming the perception challenges of non-rigid objects, a key step toward fully automated manufacturing. Kim’s research bridges foundational theory with real-world application, making him a notable figure in the ongoing effort to bring robotic dexterity to complex assembly tasks.