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About

Yusheng Xu is a pioneering figure in space robotics and autonomous systems, whose work has fundamentally shaped how robots operate in the challenging environment of space. His research spans three interconnected domains: large-scale 3D point cloud registration, space robot dynamics and control, and intelligent robotic manipulation. Xu’s most impactful contribution is his comprehensive review and benchmark on registering large-scale terrestrial laser scanner point clouds, which has garnered over 410 citations and serves as a foundational reference for the field. In space robotics, he introduced groundbreaking concepts including the normal form augmentation approach for adaptive control of free-floating space robots and developed the first systematic measure of dynamic coupling between a robot arm and its spacecraft base. His work on minimum-torque path planning using genetic algorithms and the development of the Self-Mobile Space Manipulator (SM²) demonstrate his ability to bridge theoretical advances with practical implementation. Xu also made significant contributions to compliant wrist systems for automated assembly, achieving over 100 combined citations for his work on position compensation and force control stability. His research on Hidden Markov Model-based skill learning for telerobotics has influenced how robots can learn from human operators. With over 800 total citations across his career, Xu’s work continues to inspire new generations of researchers in space robotics and autonomous manipulation.