Papers
1
Total Citations
9
H-Index
1
About
Dr. Xiaofei Yue is a leading researcher in space robotics, with a primary focus on intelligent motion planning and control for multi-arm robotic systems operating in orbital environments. Her most influential work, "Coordinated Motion Planning of Dual-arm Space Robot with Deep Reinforcement Learning" (2019, 9 citations), pioneers the integration of deep reinforcement learning with classical kinematic modeling to solve complex, real-time coordination challenges. By combining the Denavit-Hartenberg (D-H) method with rapidly-exploring random trees (RRT), Dr. Yue has developed novel frameworks that enable dual-arm robots to autonomously plan collision-free, cooperative maneuvers—critical for satellite servicing, debris removal, and in-orbit assembly. Her contributions bridge the gap between traditional robotics and modern AI, offering scalable solutions for autonomous space operations. Dr. Yue’s work is foundational for researchers exploring reinforcement learning in constrained, high-stakes environments, and her citation record reflects growing recognition in the aerospace and robotics communities. Her achievements underscore a career dedicated to advancing the autonomy and safety of next-generation space robots.
Research Focus
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Top Papers
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