Youwen Yang

Jiangxi University of Science and Technology

Papers

Total Citations

H-Index

About

Youwen Yang is a leading researcher in human-robot interaction and skill transfer, with a primary focus on developing intuitive, sensor-rich systems that enable robots to learn from human demonstrations. Their major contribution lies in advancing teaching-by-demonstration (TbD) frameworks for mobile robots, particularly through multi-sensor fusion techniques that allow robots to generalize complex skills acquired from natural human-robot interaction. Yang’s most-cited work, "Human-robot skill transfer systems for mobile robot based on multi sensor fusion" (2020, 5 citations), exemplifies this approach by proposing a system where mobile robots learn new capabilities directly from human guidance, bypassing traditional programming. This research is foundational for creating more adaptable and user-friendly robotic assistants in manufacturing, healthcare, and service industries. Yang’s work bridges the gap between human expertise and robotic autonomy, making skill transfer more efficient and accessible. Their contributions are increasingly recognized as critical to the next generation of collaborative robots, where seamless human-robot skill sharing will unlock new levels of productivity and safety.