Yuntao Li
Papers
3
Total Citations
18
H-Index
2
About
Yuntao Li is an emerging robotics researcher whose work spans space robotics, robotic manipulation, and reinforcement learning-based control systems. His research addresses some of the most technically demanding challenges in modern robotics, from the precision control of manipulators operating in the unforgiving environment of space to the development of accessible tools for training intelligent robotic systems. His most cited work, "Identification and High-Precision Trajectory Tracking Control for Space Robotic Manipulator" (2023, 13 citations), demonstrates his expertise in dynamics modeling and advanced control strategies for space-grade systems — a critical area as nations and agencies accelerate orbital operations. Complementing this, his contribution of open-source reinforcement learning environments built on MuJoCo with the Franka Panda arm (2024, 4 citations) reflects a commitment to democratizing robotics research, offering the community standardized benchmarks for push, slide, and pick-and-place tasks through the Gymnasium Robotics API. Most recently, Li has contributed to the design of a modular reconfigurable space robotic system (MRSRS) featuring a novel standard interface, PETLOCK, advancing the frontier of adaptable hardware for future space exploration missions. Across his still-developing career, Li shows a promising trajectory bridging theoretical control, physical hardware design, and learning-based robotics.
Research Focus
Key Achievements
Top Papers
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