Papers
3
Total Citations
25
H-Index
2
About
Quan An is a rising researcher in the field of space robotics, with a focus on the control and autonomy of free-floating and hybrid manipulator systems for on-orbit operations. His work addresses critical challenges in autonomous space assembly, grasping, and path planning. An’s most cited paper, "Time-Optimal Path Tracking for Dual-Arm Free-Floating Space Manipulator System Using Convex Programming" (2023, 19 citations), introduces a novel convex programming approach to solve the complex time-optimal control problem for dual-arm free-floating space manipulators, ensuring efficient and constraint-aware trajectory planning. He has further advanced the field with "Impedance control in serial-parallel hybrid space robots for assembly operations" (2025, 5 citations), which develops compliant control strategies for precise, safe interaction during assembly tasks. Most recently, An’s "SLiG-Net: A joint pose optimization network for space robot grasping under low-light conditions" (2025, 1 citation) applies deep learning to enhance robotic perception and grasping in challenging orbital lighting environments. Through these contributions, Quan An is establishing himself as a key innovator in enabling robust, autonomous manipulation for the next generation of space missions.
Research Focus
Key Achievements
Top Papers
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