Sangwoong Yoon
Papers
1
Total Citations
58
H-Index
1
About
Sangwoong Yoon is a researcher advancing the safety and autonomy of robotic systems, with a primary focus on collision detection and human-robot interaction. His most-cited work, “Collision Detection for Robot Manipulators Using Unsupervised Anomaly Detection Algorithms” (2021, 58 citations), addresses a critical challenge in collaborative robotics: enabling fast, accurate collision detection in dynamic, unstructured environments shared with humans. Yoon’s key contribution lies in developing model-based detection methods that circumvent the need for joint torque sensors, instead employing sophisticated friction modeling and unsupervised anomaly detection to identify collisions in real time. This approach is particularly valuable for lightweight, cost-effective robot manipulators operating alongside people. By tackling the practical difficulties of friction compensation, Yoon’s research enhances the reliability of safety systems in human-robot collaboration. His work is notable for bridging the gap between theoretical anomaly detection and real-world robotic applications, making robots safer and more adaptable. With growing citation impact, Yoon is establishing himself as a contributor to the next generation of intelligent, human-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1