Adam Gilmour
Papers
4
Total Citations
20
H-Index
3
About
Adam Gilmour is a researcher at the forefront of robotic non-destructive evaluation (NDE), specializing in the automation of industrial inspections. His work centers on integrating advanced sensing and robotics to overcome the limitations of traditional manual inspection, particularly for complex geometries and constrained environments. Gilmour's key contributions include developing a novel method for robotic crawler positioning using an onboard depth-sensing camera, enabling autonomous navigation in semistructured, self-similar environments for quality assurance (2023, 9 citations). He has also pioneered techniques to mitigate RGB-D camera errors for robust ultrasonic inspections by leveraging force-torque sensors, addressing payload constraints on compact robots (2024, 6 citations). Additionally, Gilmour has designed a magnetic inspection platform for teleoperated remote inspections of complex geometries (2022, 3 citations) and developed an image processing-based localization system using phased array ultrasound to precisely probe welds (2023, 2 citations). His research directly addresses industry demands for faster, more cost-effective inspections, with notable achievements in enhancing robotic autonomy and sensor accuracy. Gilmour’s work is essential reading for those interested in the intersection of robotics, computer vision, and NDE, offering practical solutions for inspecting critical infrastructure.
Research Focus
Key Achievements
Top Papers
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