Max Robotics — Global Service Robot Directory + US Certification

About

Sara Sharifzadeh’s research lies at the intersection of robotic perception, precision metrology, and industrial automation, with a focus on solving the “needle-in-a-haystack” problem of detecting tiny surface defects on massive, complex free-form parts. Her most-cited work, “Robust hand-eye calibration of 2D laser sensors using a single-plane calibration artefact” (72 citations), provides a streamlined, high-accuracy method for integrating laser scanners with robotic arms—a foundational contribution to automated inspection. She further advanced this field through “Abnormality detection strategies for surface inspection using robot mounted laser scanners” (26 citations), which systematically addresses the challenge of locating sub-millimeter flaws across multi-square-meter surfaces. Sharifzadeh’s broader portfolio includes multi-sensor robotic inspection systems and machine learning approaches for force/torque compensation in industrial robots, demonstrating versatility across sensing and control. Her work directly enables faster, more cost-effective quality control in manufacturing, where even microscopic defects can lead to critical failures. By combining rigorous calibration techniques with practical detection strategies, Sharifzadeh has established herself as a key contributor to the automation of high-precision surface inspection.