Shuangfu Suo
Papers
3
Total Citations
17
H-Index
2
About
Shuangfu Suo is a rising researcher in the field of industrial robotics and intelligent manufacturing, with a focus on trajectory optimization, robotic grasping, and dynamic modeling. His work addresses critical challenges in automation, including improving the efficiency and precision of industrial robots. His most cited paper, "Industrial Robot Trajectory Optimization Based on Improved Sparrow Search Algorithm" (2024, 10 citations), introduces a multi-strategy enhanced algorithm to reduce joint vibrations and boost operational efficiency in six-axis robots. In "A Novel Deep Learning-Based Pose Estimation Method for Robotic Grasping of Axisymmetric Bodies in Industrial Stacked Scenarios" (2022, 5 citations), Suo leverages deep learning for 6D pose estimation, enabling more reliable robotic grasping in cluttered environments—a key step toward unmanned manufacturing. His work on "Dynamic Modeling and Optimization Analysis of Rigid–Flexible Coupling Manipulator Based on Assumed Mode Method" (2024, 2 citations) tackles vibration issues in lightweight space robotic arms, advancing the design of next-generation, high-performance manipulators. With a growing citation record, Suo’s contributions are shaping the future of intelligent, efficient, and adaptive robotic systems for industrial and space applications.
Research Focus
Key Achievements
Top Papers
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