Papers
27
Total Citations
537
H-Index
13
About
Xuesong Mei is a leading researcher in robotics, with a primary focus on robot-environment interaction control, force estimation, and human-robot skill transfer. His work addresses critical challenges in making robots safer and more adaptive, particularly for manufacturing, surgical, and service applications. A key contribution is his development of an improved disturbance observer for flexible-joint robots, enabling accurate end-effector force estimation using joint torque sensors—a fundamental advance for compliant manipulation (107 citations). Mei has also pioneered optimized impedance adaptation strategies for robots interacting with unknown and flexible environments, formulating cost functions that balance tracking error and interaction force to achieve stable, high-performance contact tasks. Beyond interaction control, his research spans energy harvesting from human walking for robotic systems, bio-inspired optics (fabrication of artificial compound eyes with wide field of view), and dynamic skill learning from human demonstration using Riemannian dynamic movement primitives. His recent work on collision-free motion generation using stochastic optimization and signed distance field networks further demonstrates his commitment to safe, practical robot autonomy. With multiple highly cited papers and a growing impact in the field, Mei is recognized for advancing the theoretical and applied frontiers of robotic manipulation and human-robot collaboration.
Research Focus
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