Luyao Yuan

University of California, Los Angeles, Shandong University, Beijing Information Science & Technology University

Papers

Total Citations

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About

Luyao Yuan is a robotics researcher whose work centers on human-robot interaction, value alignment, and intelligent control systems. His most influential contribution, "In situ bidirectional human-robot value alignment" (2022, 74 citations), addresses a fundamental challenge in social robotics: enabling bidirectional communication where robots act as both receptive listeners and expressive speakers. This work is critical for robots operating in complex, multi-goal environments where task priorities vary, ensuring that human and robot partners remain synchronized in their objectives. Yuan also tackles capability calibration in "Show Me What You Can Do: Capability Calibration on Reachable Workspace for Human-Robot Collaboration" (2022, 6 citations), proposing methods to align human expectations with a robot’s true physical abilities—a key step toward effective teamwork. Earlier in his career, he developed visual servo grasping algorithms for the NAO robot in home environments (2014, 5 citations), and more recently, he has advanced anti-disturbance trajectory tracking control for wafer transfer robots using RBF neural networks (2025, 3 citations). Yuan’s work bridges foundational robotics challenges—perception, control, and social coordination—with practical applications in manufacturing and service domains, making him a versatile contributor to the field.