Xiangfeng Tan
Papers
1
Total Citations
2
H-Index
1
About
Xiangfeng Tan is a pioneering researcher in the field of robotic manipulation, with a primary focus on adaptive grasping algorithms and humanoid underactuated manipulators for agricultural applications. His work addresses a critical challenge in fruit harvesting robotics: the lack of generalizability in conventional systems that are typically designed for specific fruit types. Tan’s major contribution lies in developing a humanoid underactuated manipulator combined with an adaptive grasping algorithm that evaluates grasping adaptability and stability—key performance metrics for versatile fruit handling. His most cited paper, *"Fruit grasping evaluation based on a humanoid underactuated manipulator and an adaptive grasping algorithm"* (2025), has already garnered 2 citations, signaling early impact in this emerging field. This work represents a significant step toward creating more flexible, intelligent robotic systems capable of handling diverse agricultural produce without reprogramming. Tan’s research bridges robotics, control theory, and agricultural engineering, offering promising solutions for automated harvesting. His innovative approach to underactuated mechanisms—which mimic human hand dexterity while reducing mechanical complexity—positions him as a rising figure in the development of next-generation agricultural robots that are both efficient and adaptable.
Research Focus
Key Achievements
Top Papers
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