Papers
2
Total Citations
8
H-Index
2
About
Yufeng Yang is a robotics researcher specializing in intelligent manufacturing and precision automation, with a focus on robotic deburring and polishing technologies. His work addresses critical challenges in metal part finishing, particularly the removal of burrs—a common defect that compromises machining and assembly precision. Yang’s most cited paper, "Local Deformable Template Matching in Robotic Deburring" (2018, 6 citations), introduces a machine vision-based method that adapts to casting deformations, significantly improving the efficiency and accuracy of robotic deburring processes. This contribution is pivotal for industries requiring high-precision metal components. In his more recent work, "Design of a Novel Force Controlled Polishing Device Based on a Coupled Active-Passive Compliant Mechanism" (2023, 2 citations), Yang proposes an innovative, low-cost polishing device that integrates active and passive compliance for precise force control, advancing robotic surface finishing. Though his citation counts are modest, his research demonstrates practical impact in manufacturing automation, offering scalable solutions for real-world applications. Yang’s work is particularly valuable for students and researchers exploring compliant mechanisms and vision-guided robotics, as it bridges theoretical design with industrial implementation, laying groundwork for more adaptive and cost-effective robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Local Deformable Template Matching in Robotic Deburring6 citations · 2018
- 2