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About

Andrew J. Tickle is a researcher whose work sits at the intersection of image processing, field programmable gate arrays (FPGAs), and robotics. His primary contributions lie in the development and simulation of soft morphological operators for FPGAs, a technique that enhances image processing in noisy environments by preserving fine details better than standard methods. This work, detailed in his most-cited paper (2013, 6 citations), has implications for real-time visual systems. Tickle has also advanced autonomous navigation through dead reckoning systems for security patrol robots (2010, 3 citations), enabling simple yet effective indoor positioning. His innovative application of Morphological Scene Change Detection (MSCD) for visual leak and failure identification in process engineering (2010, 3 citations) demonstrates a cross-disciplinary approach, using FPGA-based binary differences to detect critical changes. More recently, he contributed to search and rescue robotics (2019, 2 citations), showing a commitment to practical, life-saving technologies. Though his citation counts are modest, Tickle’s work is notable for its integration of hardware-level image processing with real-world robotic systems, offering foundational insights for students and researchers in embedded systems and computer vision.