Unal Artan

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About

Unal Artan is a researcher focused on advancing automation and safety in underground mining and heavy equipment operations through innovative robotic and sensing technologies. His primary research areas include robotic mapping, localization, and human-machine interaction for challenging industrial environments. Artan's major contributions lie in developing low-cost, practical solutions for underground mine drift mapping, where satellite GPS is unavailable. His 2010 paper "Towards underground mine drift mapping with RFID" (20 citations) and 2011 work "Robotic mapping of underground mine passageways" (18 citations) address the critical challenge of real-time vehicle positioning and orientation for automation and traffic management in mines. More recently, his 2022 paper "Touchless Control of Heavy Equipment Using Low-Cost Hand Gesture Recognition" (11 citations) demonstrates a robust, inexpensive system for remote gesture-based control of heavy construction equipment, expanding human-machine interaction possibilities. Artan's work on globally consistent mapping of large-scale passageway environments (2009, 5 citations) further tackles the complex problem of identifying robot locations in GPS-denied settings. His research bridges the gap between theoretical robotics and practical, industry-directed applications, offering cost-effective solutions that enhance safety and efficiency in mining and construction.