Gabriel Probst

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About

Gabriel Probst is a leading researcher in the field of robotic X-ray computed tomography (CT), where his work is driving the transition from rigid, circular-scan systems to highly flexible, robot-arm-based inspection platforms. His core research focuses on solving a critical bottleneck in this technology: the accurate determination of scan geometry. Probst’s major contributions include the development of a reference-free method for estimating robot CT imaging geometry, a breakthrough that eliminates the need for traditional calibration phantoms and enables truly arbitrary scan trajectories. His work on geometric qualification for flexible trajectories has further established the theoretical and practical frameworks needed to prevent severe reconstruction artifacts in non-circular paths. With his most-cited papers each garnering 8 citations, Probst’s impact is evident in the foundational nature of his research, which is frequently referenced by peers tackling similar challenges in industrial non-destructive testing. By systematically investigating how robot properties—such as stiffness and repeatability—affect image quality in twin-robot CT systems, he has provided essential guidelines for system design and calibration. Probst’s achievements are paving the way for next-generation CT scanners that can adapt to complex part geometries, promising transformative advances in quality control and metrology.