Xinle Li
Papers
2
Total Citations
12
H-Index
2
About
Xinle Li is a researcher in industrial robotics, specializing in the mechanical design and structural optimization of heavy-duty robotic systems. Their work focuses on enhancing the rigidity, precision, and lifting capacity of robots used in demanding manufacturing environments, particularly in welding and palletizing applications. Li’s most-cited paper, “Static Simulation and Structure Optimization of Key Parts of Joint Welding Robots” (2018, 10 citations), addresses a critical challenge in welding automation: the inherent flexibility of serial robot arms, which compromises positioning accuracy and weld quality. By simulating and optimizing key components, Li’s work contributes to more robust and reliable welding robots. In a related study, “Structural design of a kind of palletizing robot with double-drive mechanical-arm and large lifting force” (2017, 2 citations), Li introduces a novel heavy-duty palletizing robot designed to meet the growing demand for high-efficiency, high-capacity automation in logistics and manufacturing. Though early in their career, Li’s contributions to improving robot stiffness and payload capacity are valuable for advancing industrial automation, with potential applications in automotive, aerospace, and warehousing sectors.
Research Focus
Key Achievements
Top Papers
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- 2