Peng Ouyang

Papers

Total Citations

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About

Peng Ouyang is a leading researcher in intelligent manufacturing and robotic machining, with a core focus on 3D vision-guided systems for industrial automation. His most cited work, "3D Vision-Guided Robotic Grinding Framework for Repairing Random Defects" (2025), addresses a critical gap in remanufacturing: while robotic grinding excels at global machining of large complex components, it has lacked effective solutions for local defect repair. Ouyang’s framework pioneers a vision-based approach that enables robots to autonomously detect, localize, and grind random defects, significantly enhancing precision and flexibility in repair workflows. This contribution has already garnered early citations, underscoring its relevance to sustainable manufacturing and lifecycle extension of high-value components. Beyond this, Ouyang’s research spans robotic path planning, adaptive control, and sensor integration, with implications for aerospace, automotive, and heavy machinery industries. His work is distinguished by its practical orientation—bridging advanced computer vision with real-time robotic manipulation to solve pressing industrial challenges. As a rising figure in the field, Ouyang’s innovations promise to reshape how manufacturers approach defect repair, reducing waste and downtime while boosting productivity.