Kyu Min Park

Seoul National University, Korea Institute of Science and Technology

Papers

Total Citations

162

H-Index

About

Kyu Min Park is a leading researcher in robotics, with a primary focus on collision detection for robot manipulators operating in human-shared environments. His work addresses a critical safety challenge: enabling robots to detect both sharp impacts and subtle "soft" collisions—such as pulling or catching motions—without relying on expensive joint torque sensors. Park’s major contributions include developing learning-based and unsupervised anomaly detection algorithms that use motor current data and friction modeling to identify collisions in real time. His 2020 paper on learning-based detection has garnered 97 citations, reflecting its influence on cost-effective, sensor-free safety systems. A 2021 follow-up, with 58 citations, advanced these methods by improving robustness in dynamic settings. His most recent 2023 survey synthesizes the field’s progress, offering a comprehensive roadmap for future research. Park’s work is pivotal for the safe deployment of collaborative robots in factories, homes, and healthcare, making him a key figure in human-robot interaction and industrial automation.