Martin Dierolf

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About

Martin Dierolf is a researcher advancing the field of X-ray computed tomography (CT) through innovative robotics integration. His work focuses on enhancing the flexibility and capability of CT imaging by replacing traditional, rigid sample stages with robotic manipulators. Dierolf’s major contribution lies in developing and demonstrating a seven-degree-of-freedom robotic arm as a sample holder for laboratory X-ray CT systems. This breakthrough enables non-standard, task-specific scanning trajectories that were previously impossible, allowing for more comprehensive and artifact-free imaging of complex samples. His most-cited paper, "X-ray computed tomography with seven degree of freedom robotic sample holder" (2022, 12 citations), establishes the foundational hardware and software integration. Building on this, his subsequent work on "Spherical acquisition trajectories for x-ray computed tomography with a robotic sample holder" (2023) optimizes path planning and control algorithms for seamless execution of arbitrary spherical scans. While his citation counts are early-stage, Dierolf’s work represents a significant step toward more adaptive and intelligent CT systems, with potential applications in materials science, biology, and industrial inspection. His research is particularly notable for bridging robotics and imaging, opening new avenues for non-destructive 3D analysis.