Changyan Xiao

Papers

Total Citations

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About

Changyan Xiao is a robotics and computer vision researcher whose work bridges intelligent automation and medical robotics. His research centers on two principal domains: robotic spray painting systems and image-guided robotic interventions, demonstrating a versatile command of 3D perception, machine learning, and real-world robotic applications. In the realm of industrial automation, Xiao has made notable contributions to solving practical challenges in robotic spray painting production lines. His 2021 work on online 3D modeling of complex workpieces using affordable RGB-D cameras — his most cited contribution with 18 citations — addressed the critical problem of reconstructing workpiece geometry in real time without prior models, enabling robust painting-path planning. Building on this, his 2022 study tackled accurate recognition of multiple densely arranged workpiece types on live production lines, furthering the goal of fully autonomous painting workflows. More recently, Xiao has expanded into medical robotics, developing a boundary-guided needle localization approach for MRI-guided robotic interventions, tackling the demanding challenge of precisely detecting slender needles within complex 3D tissue environments. Across his body of work, Xiao consistently demonstrates a commitment to translating low-cost, practical solutions into high-stakes robotic systems, making his research valuable to both industrial engineers and clinical robotics developers alike.