Papers
4
Total Citations
21
H-Index
2
About
Yiman Zhu is a researcher focused on advancing autonomous manipulation and perception for space robotics. Her key research areas include motion planning for free-floating and free-flying space robots, cable grasping, and on-orbit low-light image enhancement. Zhu’s major contributions center on developing intelligent planning algorithms that enable robots to track and interact with tumbling, non-cooperative targets—a critical challenge for on-orbit servicing and debris removal. She has pioneered the use of reinforcement learning for sequential optimization and two-axis matching in these complex dynamic environments, as well as introduced a novel cable-grasping planner based on operation surfaces. Her work on a ground-based dataset and diffusion model for low-light image enhancement addresses the practical limitations of space-based visible cameras, improving situational awareness during servicing missions. With her most-cited paper garnering 11 citations, Zhu’s research is gaining recognition for its innovative integration of learning-based methods with real-world space constraints. Her achievements highlight a promising trajectory in making autonomous space operations safer and more reliable.
Research Focus
Key Achievements
Top Papers
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