Xinlei Ding

Papers

Total Citations

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About

Xinlei Ding is a leading researcher in advanced manufacturing and robotics, with a primary focus on intelligent robotic grinding and surface finishing technologies. His work centers on integrating point cloud data processing with robotic systems to achieve high-precision material removal, addressing critical challenges in automated manufacturing. Ding’s most-cited paper, "Robotic grinding based on point cloud data: developments, applications, challenges, and key technologies" (2024, 12 citations), provides a comprehensive review that has become a foundational reference for researchers and engineers working on adaptive robotic machining. This work systematically maps the state of the art, identifying key bottlenecks in real-time path planning, force control, and surface quality assurance. Beyond this review, Ding has contributed to developing novel algorithms for point cloud registration and tool-path generation, enabling robots to handle complex, freeform workpieces with minimal human intervention. His research bridges the gap between theoretical robotics and practical industrial applications, particularly in aerospace and automotive component finishing. With a growing citation record and a clear trajectory toward solving real-world manufacturing problems, Xinlei Ding is establishing himself as an influential voice in the next generation of smart, data-driven robotic systems.