Mark Sutcliffe
Papers
5
Total Citations
32
H-Index
3
About
Mark Sutcliffe is a researcher specializing in robotics, autonomous systems, and Non-Destructive Testing (NDT), with a particular focus on advancing ultrasonic inspection methodologies for complex and safety-critical structures. His work sits at the intersection of robotics and structural integrity assessment, addressing real-world challenges in aerospace, remanufacturing, and offshore energy sectors. Sutcliffe's most influential contribution, the LPAS framework — Locate, Plan, Approach, Scan — represents a significant leap forward in autonomous robotic NDT, eliminating the traditional dependency on costly digital twins by leveraging low-cost vision sensors for real-time path planning. This work has garnered 12 citations since 2022, reflecting its immediate relevance to the field. Complementing this, his novel complete-surface-finding algorithm (10 citations) enables online scanning of components with irregular or previously unmeasured geometries, a critical capability in adaptive manufacturing environments. His earlier research on automated Full Matrix Capture for mooring chain inspection demonstrates a commitment to applying advanced ultrasonic techniques to offshore infrastructure safety. More recently, his graph theory and K-dimensional tree optimisation approach to path planning further underscores his drive toward computationally efficient, fully autonomous inspection systems — positioning him as an emerging voice in intelligent robotic NDT research.
Research Focus
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Top Papers
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